#eval=params$runcodebooks

eas_20 %>%    select_if(function(col) {!is.character(col) | n_distinct(as.numeric(col))<15}) %>%
 # detect_scales(quiet=TRUE) %>% 
codebook(., survey_repetition = "single", metadata_table = TRUE) #Gerhard: this could also create an html; or make this as a separate markdown. It takes a long time to run... so maybe don't do it here

Metadata

Description

Dataset name: .

The dataset has N=2164 rows and 310 columns. 0 rows have no missing values on any column.

Metadata for search engines
  • Date published: 2021-03-03
x
respondentid
collectorid
start_date
end_date
custom_data_1
opt_out_cea
first_hear_ea_other
first_hear_ea_desc
involve_80k
involve_givewell
involve_personal_contact
involve_book
involve_article_blog
involve_gwwc
involve_group
involve_online
involve_lesswrong
involve_slate_star
involve_podcast
involve_ea_global
involve_lycs
involve_ace
involve_eagx
involve_other
action_chose_job_degree
action_applied_job_degree
action_donated
action_gwwc
action_organize_group
action_work_ea_org
action_change_major
action_wrote_thesis
action_internship
action_applied_ea_global
action_attended_ea_global
action_ea_forum
action_lead_group
action_applied_one_on_one
action_had_one_on_one
action_change_career
action_subscribe_80k
action_none
ea_org_or_project
member_ea_fb
member_ea_forum
member_lesswrong
member_ea_group
member_none
local_group_original
group_comfortable_friend
group_beliefs_humility
group_supports_action
influence_80k_one_on_one
influence_80k_website
influence_80k_podcast
influence_podcast_other
influence_personal_contact
influence_books
influence_gwwc
influence_local_group
influence_givewell
influence_ea_global
influence_eagx
influence_ace
influence_lycs
influence_ea_forum
influence_articles_blogs
influence_ea_survey
influence_facebook_groups
influence_lesswrong
influence_slate_star
influence_wanbam
influence_aac
influence_none
influence_other
negative_80k
negative_podcast
negative_givewell
negative_personal_contact
negative_books
negative_gwwc
negative_local_group
negative_lesswrong
negative_slate_star
negative_ea_global
negative_eagx
negative_facebook_group
negative_ea_forum
negative_articles_blogs
negative_ea_fellowship
negative_eagx2
negative_ea_newsletter
negative_wanbam
negative_none
negative_other
negative_response
engaged_ea_forum
engaged_online_community
engaged_local_groups
engaged_ea_fellowship
engaged_gwwc
engaged_ea_global
engaged_eagx
engaged_ea_newsletter
engaged_wanbam
engaged_personal_contact
engaged_80k_podcast
engaged_80k_hours
engaged_80k_one_on_one
engaged_givewell
engaged_lesswrong
engaged_slate_star
substantial_affect_impact
prioritize_animal_welfare
prioritize_causes
prioritize_climate_change
prioritize_biosecurity
prioritize_nuclear_security
prioritize_ai_risks
prioritize_mental_health
prioritize_global_poverty
prioritize_meta
prioritize_ea_movement
prioritize_x_risks
prioritize_broad_longtermism
prioritize_other
currency
currency_other
income
donation_2019
donation_2020
donate_later
university_original
birth_year
gender_original
sexual_orientation
country
city_other
ea_community_ideal
ea_community_satisfaction
ea_community_why
agree_ea_helps_impact
agree_part_of_ea_community
friend_introduce
learned_80k
connection_80k
learned_ea_global
connection_ea_global
learned_ea_hub
connection_ea_hub
learned_ea_student_mentoring
connection_ea_student_mentor
learned_eagx
connection_eagx
learned_effective_thesis
connection_effective_thesis
learned_facebook_group
connection_facebook_group
learned_gwwc
connection_gwwc
learned_intl_ea_events
connection_intl_ea_events
learned_personal_connection
connection_personal_contact
learned_lesswrong
connection_lesswrong
learned_local_group
connection_local_groups
learned_non_local_group
connection_non_local_group
learned_ea_forum
connection_ea_forum
learned_ea_books
connection_ea_books
learned_ea_newsletter
connection_ea_newsletter
learned_none
connection_none
learned_connection_other
participate_doing_good_better
participate_the_precipice
participate_fellowship_intro
participate_fellowship_adv
participate_80k_pod_discuss
participate_fellowship_career
participate_fellowship_causes
participate_intro_one_on_one
participate_gwwc_info_session
participate_donation_discuss
participate_social_event
participate_contact
email_next_survey
email_followup_surveys
email_dont_email
share_80k
dont_share_80k
profile_ea_hub
agree_quantify_compare_impact
agree_ways_better_than_others
agree_work_on_any_cause
agree_farmed_animals_concern
agree_longtermism
reputation_effect_explanation
bottleneck_productivity
dislike_ea_community
donate_rethink_charity
donate_80k
donate_center_applied_rational
donate_mercy_for_animals
donate_other1
donate_other2
donate_other3
donate_other4
donate_other5
datecreated
group_name_original
group_name_manual
first_hear_qual
_merge
ea_id
ea_id2
ea_id3
engagement
capital_over_impact
financial_instability
first_generation_student
reputation_effect
year_involved
first_hear_ea
city
collector_source
gender_manual
race_white
race_black_aa
race_hispanic_la_spanish
race_american_indian_alaskan
race_asian
race_native_hawaiin_pacific
race_prefer_no_answer
race_other
race_
status_employed_ft
status_employed_pt
status_self_employed
status_not_employed_looking
status_not_employed
status_homemaker_parent
status_retired
status_student_hs
status_student_undergrad
status_student_masters
status_student_doctoral
status_student_other
status_prefer_no_answer
status_
career_still_deciding
career_building_capital
career_non_profit_ea
career_non_profit
career_for_profit_earn_to_give
career_for_profit
career_academia
career_government
career_think_tank_lobby
career_na
career_other
career_
race
age_approx
employ_status
age_approx_ranges
age_approx_split
engagement_num
engagement_f
d_engage_3_5
d_engage_4_5
d_engage_5
income_k
d_male
d_student
d_live_usa
prioritize_lt
referrer
referrer_cat
referrer_min100
referrer_cat2
referrer_cat3
engage_cats_1
engage_cats_2
start_date_quantiles
start_date_thirds_by_referrer
survey_willing
donation_2019_c
donation_2020_c
income_c
income_k_c
income_c_imp
don_share_inc_19
don_share_inc_19_imp
don_19_p1
income_c_imp_k
action_gwwc_f
top_priority_rating
avg_priority_rating
mn_priority_rating
lt_top_priority
lt_above_mn_priority
top_priority_rating_among_lt
mn_priority_lt_rating
start_date_qtl_by_referrer

#Variables

respondentid

Respondent ID

Distribution

Distribution of values for respondentid

Distribution of values for respondentid

0 missing values.

Summary statistics

name label data_type n_missing complete_rate min median max mean sd hist
respondentid Respondent ID numeric 0 1 1.2e+10 1.2e+10 1.2e+10 1.2e+10 31898517 ▆▆▇▃▂

collectorid

Collector ID

Distribution

Distribution of values for collectorid

Distribution of values for collectorid

0 missing values.

Summary statistics

name label data_type n_missing complete_rate min median max mean sd hist
collectorid Collector ID numeric 0 1 4e+08 4e+08 4e+08 4e+08 407595 ▇▂▂▁▁

start_date

Start Date

Distribution

## 52  unique, categorical values, so not shown.

0 missing values.

Summary statistics

name label data_type n_missing complete_rate n_unique min median max
start_date Start Date Date 0 1 52 2020-11-13 2020-12-05 2021-01-03

end_date

End Date

Distribution

## 52  unique, categorical values, so not shown.

0 missing values.

Summary statistics

name label data_type n_missing complete_rate n_unique min median max
end_date End Date Date 0 1 52 2020-11-13 2020-12-05 2021-01-03

custom_data_1

Custom Data 1

Distribution

## No non-missing values to show.

2164 missing values.

Summary statistics

name label data_type n_missing complete_rate min median max hist
custom_data_1 Custom Data 1 numeric 2164 0 NA NA NA

opt_out_cea

Opt out of data sharing with the Centre for Effective Altruism

Distribution

Distribution of values for opt_out_cea

Distribution of values for opt_out_cea

0 missing values.

Summary statistics

name label data_type n_missing complete_rate n_unique empty min max whitespace
opt_out_cea Opt out of data sharing with the Centre for Effective Altruism character 0 1 2 2046 0 78 0

first_hear_ea_other

How did you first hear about effective altruism? Other

Distribution

Distribution of values for first_hear_ea_other

Distribution of values for first_hear_ea_other

1997 missing values.

Summary statistics

name label data_type n_missing complete_rate n_unique empty min max whitespace
first_hear_ea_other How did you first hear about effective altruism? Other character 1997 0.08 145 0 3 339 0

first_hear_ea_desc

Please briefly specify any further details about how you first heard about EA.

Distribution

Distribution of values for first_hear_ea_desc

Distribution of values for first_hear_ea_desc

968 missing values.

Summary statistics

name label data_type n_missing complete_rate n_unique empty min max whitespace
first_hear_ea_desc Please briefly specify any further details about how you first heard about EA. character 968 0.55 1144 0 1 609 0

involve_80k

Important for you getting involved in EA? 80,000 Hours

Distribution

Distribution of values for involve_80k

Distribution of values for involve_80k

290 missing values.

Summary statistics

name label data_type n_missing complete_rate min median max mean sd hist
involve_80k Important for you getting involved in EA? 80,000 Hours numeric 290 0.87 0 1 1 0.51 0.5 ▇▁▁▁▇

involve_givewell

Important for you getting involved in EA? GiveWell

Distribution

Distribution of values for involve_givewell

Distribution of values for involve_givewell

290 missing values.

Summary statistics

name label data_type n_missing complete_rate min median max mean sd hist
involve_givewell Important for you getting involved in EA? GiveWell numeric 290 0.87 0 0 1 0.35 0.48 ▇▁▁▁▅

involve_personal_contact

Important for you getting involved in EA? Personal contact with EAs

Distribution

Distribution of values for involve_personal_contact

Distribution of values for involve_personal_contact

290 missing values.

Summary statistics

name label data_type n_missing complete_rate min median max mean sd hist
involve_personal_contact Important for you getting involved in EA? Personal contact with EAs numeric 290 0.87 0 0 1 0.35 0.48 ▇▁▁▁▅

involve_book

Important for you getting involved in EA? A book

Distribution

Distribution of values for involve_book

Distribution of values for involve_book

290 missing values.

Summary statistics

name label data_type n_missing complete_rate min median max mean sd hist
involve_book Important for you getting involved in EA? A book numeric 290 0.87 0 0 1 0.23 0.42 ▇▁▁▁▂

involve_article_blog

Important for you getting involved in EA? An article or blog

Distribution

Distribution of values for involve_article_blog

Distribution of values for involve_article_blog

290 missing values.

Summary statistics

name label data_type n_missing complete_rate min median max mean sd hist
involve_article_blog Important for you getting involved in EA? An article or blog numeric 290 0.87 0 0 1 0.17 0.37 ▇▁▁▁▂

involve_gwwc

Important for you getting involved in EA? Giving What We Can

Distribution

Distribution of values for involve_gwwc

Distribution of values for involve_gwwc

290 missing values.

Summary statistics

name label data_type n_missing complete_rate min median max mean sd hist
involve_gwwc Important for you getting involved in EA? Giving What We Can numeric 290 0.87 0 0 1 0.21 0.41 ▇▁▁▁▂

involve_group

Important for you getting involved in EA? Local or university EA Group

Distribution

Distribution of values for involve_group

Distribution of values for involve_group

290 missing values.

Summary statistics

name label data_type n_missing complete_rate min median max mean sd hist
involve_group Important for you getting involved in EA? Local or university EA Group numeric 290 0.87 0 0 1 0.29 0.45 ▇▁▁▁▃

involve_online

Important for you getting involved in EA? The online EA community

Distribution

Distribution of values for involve_online

Distribution of values for involve_online

290 missing values.

Summary statistics

name label data_type n_missing complete_rate min median max mean sd hist
involve_online Important for you getting involved in EA? The online EA community numeric 290 0.87 0 0 1 0.2 0.4 ▇▁▁▁▂

involve_lesswrong

Important for you getting involved in EA? LessWrong

Distribution

Distribution of values for involve_lesswrong

Distribution of values for involve_lesswrong

290 missing values.

Summary statistics

name label data_type n_missing complete_rate min median max mean sd hist
involve_lesswrong Important for you getting involved in EA? LessWrong numeric 290 0.87 0 0 1 0.18 0.39 ▇▁▁▁▂

involve_slate_star

Important for you getting involved in EA? Slate Star Codex

Distribution

Distribution of values for involve_slate_star

Distribution of values for involve_slate_star

290 missing values.

Summary statistics

name label data_type n_missing complete_rate min median max mean sd hist
involve_slate_star Important for you getting involved in EA? Slate Star Codex numeric 290 0.87 0 0 1 0.17 0.38 ▇▁▁▁▂

involve_podcast

Important for you getting involved in EA? Podcast

Distribution

Distribution of values for involve_podcast

Distribution of values for involve_podcast

290 missing values.

Summary statistics

name label data_type n_missing complete_rate min median max mean sd hist
involve_podcast Important for you getting involved in EA? Podcast numeric 290 0.87 0 0 1 0.2 0.4 ▇▁▁▁▂

involve_ea_global

Important for you getting involved in EA? EA Global

Distribution

Distribution of values for involve_ea_global

Distribution of values for involve_ea_global

290 missing values.

Summary statistics

name label data_type n_missing complete_rate min median max mean sd hist
involve_ea_global Important for you getting involved in EA? EA Global numeric 290 0.87 0 0 1 0.1 0.3 ▇▁▁▁▁

involve_lycs

Important for you getting involved in EA? The Life You Can Save

Distribution

Distribution of values for involve_lycs

Distribution of values for involve_lycs

290 missing values.

Summary statistics

name label data_type n_missing complete_rate min median max mean sd hist
involve_lycs Important for you getting involved in EA? The Life You Can Save numeric 290 0.87 0 0 1 0.12 0.33 ▇▁▁▁▁

involve_ace

Important for you getting involved in EA? Animal Charity Evaluators

Distribution

Distribution of values for involve_ace

Distribution of values for involve_ace

290 missing values.

Summary statistics

name label data_type n_missing complete_rate min median max mean sd hist
involve_ace Important for you getting involved in EA? Animal Charity Evaluators numeric 290 0.87 0 0 1 0.06 0.23 ▇▁▁▁▁

involve_eagx

Important for you getting involved in EA? EAGx

Distribution

Distribution of values for involve_eagx

Distribution of values for involve_eagx

290 missing values.

Summary statistics

name label data_type n_missing complete_rate min median max mean sd hist
involve_eagx Important for you getting involved in EA? EAGx numeric 290 0.87 0 0 1 0.07 0.26 ▇▁▁▁▁

involve_other

Important for you getting involved in EA? Other (please specify)

Distribution

Distribution of values for involve_other

Distribution of values for involve_other

290 missing values.

Summary statistics

name label data_type n_missing complete_rate min median max mean sd hist
involve_other Important for you getting involved in EA? Other (please specify) numeric 290 0.87 0 0 1 0.1 0.3 ▇▁▁▁▁

action_chose_job_degree

Action: Chose a job or graduate degree program based on EA principles

Distribution

Distribution of values for action_chose_job_degree

Distribution of values for action_chose_job_degree

280 missing values.

Summary statistics

name label data_type n_missing complete_rate min median max mean sd hist
action_chose_job_degree Action: Chose a job or graduate degree program based on EA principles numeric 280 0.87 0 0 1 0.28 0.45 ▇▁▁▁▃

action_applied_job_degree

Action: Applied for a job or graduate degree program based on EA principles

Distribution

Distribution of values for action_applied_job_degree

Distribution of values for action_applied_job_degree

280 missing values.

Summary statistics

name label data_type n_missing complete_rate min median max mean sd hist
action_applied_job_degree Action: Applied for a job or graduate degree program based on EA principles numeric 280 0.87 0 0 1 0.28 0.45 ▇▁▁▁▃

action_donated

Action: Donated >10% of your income based on EA principles

Distribution

Distribution of values for action_donated

Distribution of values for action_donated

280 missing values.

Summary statistics

name label data_type n_missing complete_rate min median max mean sd hist
action_donated Action: Donated >10% of your income based on EA principles numeric 280 0.87 0 0 1 0.32 0.47 ▇▁▁▁▃

action_gwwc

Action: Took the Giving What We Can pledge

Distribution

Distribution of values for action_gwwc

Distribution of values for action_gwwc

280 missing values.

Summary statistics

name label data_type n_missing complete_rate min median max mean sd hist
action_gwwc Action: Took the Giving What We Can pledge numeric 280 0.87 0 0 1 0.3 0.46 ▇▁▁▁▃

action_organize_group

Action: Spent >6 hours/week for >=2 months organizing an EA group/project

Distribution

Distribution of values for action_organize_group

Distribution of values for action_organize_group

280 missing values.

Summary statistics

name label data_type n_missing complete_rate min median max mean sd hist
action_organize_group Action: Spent >6 hours/week for >=2 months organizing an EA group/project numeric 280 0.87 0 0 1 0.24 0.42 ▇▁▁▁▂

action_work_ea_org

Action: Worked (or currently work) at an EA organization

Distribution

Distribution of values for action_work_ea_org

Distribution of values for action_work_ea_org

280 missing values.

Summary statistics

name label data_type n_missing complete_rate min median max mean sd hist
action_work_ea_org Action: Worked (or currently work) at an EA organization numeric 280 0.87 0 0 1 0.16 0.37 ▇▁▁▁▂

action_change_major

Action: Changed your major in university based on EA principles

Distribution

Distribution of values for action_change_major

Distribution of values for action_change_major

280 missing values.

Summary statistics

name label data_type n_missing complete_rate min median max mean sd hist
action_change_major Action: Changed your major in university based on EA principles numeric 280 0.87 0 0 1 0.09 0.29 ▇▁▁▁▁

action_wrote_thesis

Action: Wrote a thesis based on EA principles

Distribution

Distribution of values for action_wrote_thesis

Distribution of values for action_wrote_thesis

280 missing values.

Summary statistics

name label data_type n_missing complete_rate min median max mean sd hist
action_wrote_thesis Action: Wrote a thesis based on EA principles numeric 280 0.87 0 0 1 0.05 0.22 ▇▁▁▁▁

action_internship

Action: Internship related to a career path you are exploring based on EA

Distribution

Distribution of values for action_internship

Distribution of values for action_internship

280 missing values.

Summary statistics

name label data_type n_missing complete_rate min median max mean sd hist
action_internship Action: Internship related to a career path you are exploring based on EA numeric 280 0.87 0 0 1 0.12 0.33 ▇▁▁▁▁

action_applied_ea_global

Action: Applied to EA Global

Distribution

Distribution of values for action_applied_ea_global

Distribution of values for action_applied_ea_global

280 missing values.

Summary statistics

name label data_type n_missing complete_rate min median max mean sd hist
action_applied_ea_global Action: Applied to EA Global numeric 280 0.87 0 0 1 0.28 0.45 ▇▁▁▁▃

action_attended_ea_global

Action: Attended EA Global

Distribution

Distribution of values for action_attended_ea_global

Distribution of values for action_attended_ea_global

280 missing values.

Summary statistics

name label data_type n_missing complete_rate min median max mean sd hist
action_attended_ea_global Action: Attended EA Global numeric 280 0.87 0 0 1 0.29 0.45 ▇▁▁▁▃

action_ea_forum

Action: Posted or commented on the EA Forum

Distribution

Distribution of values for action_ea_forum

Distribution of values for action_ea_forum

280 missing values.

Summary statistics

name label data_type n_missing complete_rate min median max mean sd hist
action_ea_forum Action: Posted or commented on the EA Forum numeric 280 0.87 0 0 1 0.26 0.44 ▇▁▁▁▃

action_lead_group

Action: Been a leader of a local EA group

Distribution

Distribution of values for action_lead_group

Distribution of values for action_lead_group

280 missing values.

Summary statistics

name label data_type n_missing complete_rate min median max mean sd hist
action_lead_group Action: Been a leader of a local EA group numeric 280 0.87 0 0 1 0.21 0.41 ▇▁▁▁▂

action_applied_one_on_one

Action: Applied for a one-on-one career discussion with 80,000 Hours

Distribution

Distribution of values for action_applied_one_on_one

Distribution of values for action_applied_one_on_one

280 missing values.

Summary statistics

name label data_type n_missing complete_rate min median max mean sd hist
action_applied_one_on_one Action: Applied for a one-on-one career discussion with 80,000 Hours numeric 280 0.87 0 0 1 0.21 0.41 ▇▁▁▁▂

action_had_one_on_one

Action: Had a one-on-one career discussion with 80,000 Hours

Distribution

Distribution of values for action_had_one_on_one

Distribution of values for action_had_one_on_one

280 missing values.

Summary statistics

name label data_type n_missing complete_rate min median max mean sd hist
action_had_one_on_one Action: Had a one-on-one career discussion with 80,000 Hours numeric 280 0.87 0 0 1 0.13 0.33 ▇▁▁▁▁

action_change_career

Action: Changed your career plans based on EA principles

Distribution

Distribution of values for action_change_career

Distribution of values for action_change_career

280 missing values.

Summary statistics

name label data_type n_missing complete_rate min median max mean sd hist
action_change_career Action: Changed your career plans based on EA principles numeric 280 0.87 0 0 1 0.44 0.5 ▇▁▁▁▆

action_subscribe_80k

Action: Subscribed to the 80,000 Hours newsletter

Distribution

Distribution of values for action_subscribe_80k

Distribution of values for action_subscribe_80k

280 missing values.

Summary statistics

name label data_type n_missing complete_rate min median max mean sd hist
action_subscribe_80k Action: Subscribed to the 80,000 Hours newsletter numeric 280 0.87 0 1 1 0.53 0.5 ▇▁▁▁▇

action_none

Action: None of the above

Distribution

Distribution of values for action_none

Distribution of values for action_none

280 missing values.

Summary statistics

name label data_type n_missing complete_rate min median max mean sd hist
action_none Action: None of the above numeric 280 0.87 0 0 1 0.13 0.33 ▇▁▁▁▁

ea_org_or_project

Name of EA org/project you worked on or interned for.

Distribution

Distribution of values for ea_org_or_project

Distribution of values for ea_org_or_project

1719 missing values.

Summary statistics

name label data_type n_missing complete_rate n_unique empty min max whitespace
ea_org_or_project Name of EA org/project you worked on or interned for. character 1719 0.21 387 0 3 403 0

member_ea_fb

Which of the following are you a member of? EA Facebook group

Distribution

Distribution of values for member_ea_fb

Distribution of values for member_ea_fb

310 missing values.

Summary statistics

name label data_type n_missing complete_rate min median max mean sd hist
member_ea_fb Which of the following are you a member of? EA Facebook group numeric 310 0.86 0 0 1 0.48 0.5 ▇▁▁▁▇

member_ea_forum

Which of the following are you a member of? The Effective Altruism Forum

Distribution

Distribution of values for member_ea_forum

Distribution of values for member_ea_forum

310 missing values.

Summary statistics

name label data_type n_missing complete_rate min median max mean sd hist
member_ea_forum Which of the following are you a member of? The Effective Altruism Forum numeric 310 0.86 0 0 1 0.38 0.49 ▇▁▁▁▅

member_lesswrong

Which of the following are you a member of? LessWrong

Distribution

Distribution of values for member_lesswrong

Distribution of values for member_lesswrong

310 missing values.

Summary statistics

name label data_type n_missing complete_rate min median max mean sd hist
member_lesswrong Which of the following are you a member of? LessWrong numeric 310 0.86 0 0 1 0.23 0.42 ▇▁▁▁▂

member_ea_group

Which of the following are you a member of? Local EA group

Distribution

Distribution of values for member_ea_group

Distribution of values for member_ea_group

310 missing values.

Summary statistics

name label data_type n_missing complete_rate min median max mean sd hist
member_ea_group Which of the following are you a member of? Local EA group numeric 310 0.86 0 0 1 0.5 0.5 ▇▁▁▁▇

member_none

Which of the following are you a member of? None of the above

Distribution

Distribution of values for member_none

Distribution of values for member_none

310 missing values.

Summary statistics

name label data_type n_missing complete_rate min median max mean sd hist
member_none Which of the following are you a member of? None of the above numeric 310 0.86 0 0 1 0.25 0.44 ▇▁▁▁▃

local_group_original

If you are a member of a local EA group, which group are you a member of?

Distribution

Distribution of values for local_group_original

Distribution of values for local_group_original

1294 missing values.

Summary statistics

name label data_type n_missing complete_rate n_unique empty min max whitespace
local_group_original If you are a member of a local EA group, which group are you a member of? character 1294 0.4 442 0 5 324 0

group_comfortable_friend

My group is a place to which I’d feel comfortable bringing a friend

Distribution

Distribution of values for group_comfortable_friend

Distribution of values for group_comfortable_friend

1290 missing values.

Summary statistics

name label data_type ordered value_labels n_missing complete_rate n_unique top_counts
group_comfortable_friend My group is a place to which I’d feel comfortable bringing a friend factor FALSE
    1. Strongly disagree,
      2. (2) Disagree,
      3. (3) Neither agree nor disagree,
      4. (4) Agree,
      5. (5) Strongly agree
1290 0.4 5 (5): 448, (4): 310, (3): 87, (2): 22

group_beliefs_humility

My group is a place where people express their beliefs with humility

Distribution

Distribution of values for group_beliefs_humility

Distribution of values for group_beliefs_humility

1300 missing values.

Summary statistics

name label data_type ordered value_labels n_missing complete_rate n_unique top_counts
group_beliefs_humility My group is a place where people express their beliefs with humility factor FALSE
    1. Strongly disagree,
      2. (2) Disagree,
      3. (3) Neither agree nor disagree,
      4. (4) Agree,
      5. (5) Strongly agree
1300 0.4 5 (4): 388, (5): 302, (3): 143, (2): 25

group_supports_action

My group supports me in taking action based on EA principles

Distribution

Distribution of values for group_supports_action

Distribution of values for group_supports_action

1297 missing values.

Summary statistics

name label data_type ordered value_labels n_missing complete_rate n_unique top_counts
group_supports_action My group supports me in taking action based on EA principles factor FALSE
    1. Strongly disagree,
      2. (2) Disagree,
      3. (3) Neither agree nor disagree,
      4. (4) Agree,
      5. (5) Strongly agree
1297 0.4 5 (5): 404, (4): 336, (3): 111, (2): 12

influence_80k_one_on_one

Influence your ability to make impact? 80,000 Hours (1-on-1 career discussion)

Distribution

Distribution of values for influence_80k_one_on_one

Distribution of values for influence_80k_one_on_one

413 missing values.

Summary statistics

name label data_type n_missing complete_rate min median max mean sd hist
influence_80k_one_on_one Influence your ability to make impact? 80,000 Hours (1-on-1 career discussion) numeric 413 0.81 0 0 1 0.04 0.19 ▇▁▁▁▁

influence_80k_website

Influence your ability to make impact? 80,000 Hours (website)

Distribution

Distribution of values for influence_80k_website

Distribution of values for influence_80k_website

413 missing values.

Summary statistics

name label data_type n_missing complete_rate min median max mean sd hist
influence_80k_website Influence your ability to make impact? 80,000 Hours (website) numeric 413 0.81 0 0 1 0.37 0.48 ▇▁▁▁▅

influence_80k_podcast

Influence your ability to make impact? 80,000 Hours (podcast)

Distribution

Distribution of values for influence_80k_podcast

Distribution of values for influence_80k_podcast

413 missing values.

Summary statistics

name label data_type n_missing complete_rate min median max mean sd hist
influence_80k_podcast Influence your ability to make impact? 80,000 Hours (podcast) numeric 413 0.81 0 0 1 0.21 0.4 ▇▁▁▁▂

influence_podcast_other

Influence your ability to make impact? Podcast (other than 80,000 Hours)

Distribution

Distribution of values for influence_podcast_other

Distribution of values for influence_podcast_other

413 missing values.

Summary statistics

name label data_type n_missing complete_rate min median max mean sd hist
influence_podcast_other Influence your ability to make impact? Podcast (other than 80,000 Hours) numeric 413 0.81 0 0 1 0.09 0.28 ▇▁▁▁▁

influence_personal_contact

Influence your ability to make impact? Personal contact with EAs

Distribution

Distribution of values for influence_personal_contact

Distribution of values for influence_personal_contact

413 missing values.

Summary statistics

name label data_type n_missing complete_rate min median max mean sd hist
influence_personal_contact Influence your ability to make impact? Personal contact with EAs numeric 413 0.81 0 0 1 0.39 0.49 ▇▁▁▁▅

influence_books

Influence your ability to make impact? Books related to EA

Distribution

Distribution of values for influence_books

Distribution of values for influence_books

413 missing values.

Summary statistics

name label data_type n_missing complete_rate min median max mean sd hist
influence_books Influence your ability to make impact? Books related to EA numeric 413 0.81 0 0 1 0.21 0.41 ▇▁▁▁▂

influence_gwwc

Influence your ability to make impact? Giving What We Can

Distribution

Distribution of values for influence_gwwc

Distribution of values for influence_gwwc

413 missing values.

Summary statistics

name label data_type n_missing complete_rate min median max mean sd hist
influence_gwwc Influence your ability to make impact? Giving What We Can numeric 413 0.81 0 0 1 0.14 0.35 ▇▁▁▁▁

influence_local_group

Influence your ability to make impact? Local EA groups

Distribution

Distribution of values for influence_local_group

Distribution of values for influence_local_group

413 missing values.

Summary statistics

name label data_type n_missing complete_rate min median max mean sd hist
influence_local_group Influence your ability to make impact? Local EA groups numeric 413 0.81 0 0 1 0.26 0.44 ▇▁▁▁▃

influence_givewell

Influence your ability to make impact? GiveWell

Distribution

Distribution of values for influence_givewell

Distribution of values for influence_givewell

413 missing values.

Summary statistics

name label data_type n_missing complete_rate min median max mean sd hist
influence_givewell Influence your ability to make impact? GiveWell numeric 413 0.81 0 0 1 0.32 0.47 ▇▁▁▁▃

influence_ea_global

Influence your ability to make impact? EA Global

Distribution

Distribution of values for influence_ea_global

Distribution of values for influence_ea_global

413 missing values.

Summary statistics

name label data_type n_missing complete_rate min median max mean sd hist
influence_ea_global Influence your ability to make impact? EA Global numeric 413 0.81 0 0 1 0.1 0.3 ▇▁▁▁▁

influence_eagx

Influence your ability to make impact? EAGx

Distribution

Distribution of values for influence_eagx

Distribution of values for influence_eagx

413 missing values.

Summary statistics

name label data_type n_missing complete_rate min median max mean sd hist
influence_eagx Influence your ability to make impact? EAGx numeric 413 0.81 0 0 1 0.06 0.24 ▇▁▁▁▁

influence_ace

Influence your ability to make impact? Animal Charity Evaluators

Distribution

Distribution of values for influence_ace

Distribution of values for influence_ace

413 missing values.

Summary statistics

name label data_type n_missing complete_rate min median max mean sd hist
influence_ace Influence your ability to make impact? Animal Charity Evaluators numeric 413 0.81 0 0 1 0.06 0.24 ▇▁▁▁▁

influence_lycs

Influence your ability to make impact? The Life You Can Save

Distribution

Distribution of values for influence_lycs

Distribution of values for influence_lycs

413 missing values.

Summary statistics

name label data_type n_missing complete_rate min median max mean sd hist
influence_lycs Influence your ability to make impact? The Life You Can Save numeric 413 0.81 0 0 1 0.09 0.28 ▇▁▁▁▁

influence_ea_forum

Influence your ability to make impact? The EA Forum

Distribution

Distribution of values for influence_ea_forum

Distribution of values for influence_ea_forum

413 missing values.

Summary statistics

name label data_type n_missing complete_rate min median max mean sd hist
influence_ea_forum Influence your ability to make impact? The EA Forum numeric 413 0.81 0 0 1 0.12 0.33 ▇▁▁▁▁

influence_articles_blogs

Influence your ability to make impact? Articles/blogs related to EA

Distribution

Distribution of values for influence_articles_blogs

Distribution of values for influence_articles_blogs

413 missing values.

Summary statistics

name label data_type n_missing complete_rate min median max mean sd hist
influence_articles_blogs Influence your ability to make impact? Articles/blogs related to EA numeric 413 0.81 0 0 1 0.15 0.36 ▇▁▁▁▂

influence_ea_survey

Influence your ability to make impact? The EA Newsletter

Distribution

Distribution of values for influence_ea_survey

Distribution of values for influence_ea_survey

413 missing values.

Summary statistics

name label data_type n_missing complete_rate min median max mean sd hist
influence_ea_survey Influence your ability to make impact? The EA Newsletter numeric 413 0.81 0 0 1 0.06 0.23 ▇▁▁▁▁

influence_facebook_groups

Influence your ability to make impact? Facebook groups related to EA

Distribution

Distribution of values for influence_facebook_groups

Distribution of values for influence_facebook_groups

413 missing values.

Summary statistics

name label data_type n_missing complete_rate min median max mean sd hist
influence_facebook_groups Influence your ability to make impact? Facebook groups related to EA numeric 413 0.81 0 0 1 0.07 0.26 ▇▁▁▁▁

influence_lesswrong

Influence your ability to make impact? LessWrong

Distribution

Distribution of values for influence_lesswrong

Distribution of values for influence_lesswrong

413 missing values.

Summary statistics

name label data_type n_missing complete_rate min median max mean sd hist
influence_lesswrong Influence your ability to make impact? LessWrong numeric 413 0.81 0 0 1 0.12 0.32 ▇▁▁▁▁

influence_slate_star

Influence your ability to make impact? Slate Star Codex

Distribution

Distribution of values for influence_slate_star

Distribution of values for influence_slate_star

413 missing values.

Summary statistics

name label data_type n_missing complete_rate min median max mean sd hist
influence_slate_star Influence your ability to make impact? Slate Star Codex numeric 413 0.81 0 0 1 0.12 0.32 ▇▁▁▁▁

influence_wanbam

Influence your ability to make impact? WANBAM

Distribution

Distribution of values for influence_wanbam

Distribution of values for influence_wanbam

413 missing values.

Summary statistics

name label data_type n_missing complete_rate min median max mean sd hist
influence_wanbam Influence your ability to make impact? WANBAM numeric 413 0.81 0 0 1 0.01 0.1 ▇▁▁▁▁

influence_aac

Influence your ability to make impact? Animal Advocacy Careers

Distribution

Distribution of values for influence_aac

Distribution of values for influence_aac

413 missing values.

Summary statistics

name label data_type n_missing complete_rate min median max mean sd hist
influence_aac Influence your ability to make impact? Animal Advocacy Careers numeric 413 0.81 0 0 1 0.01 0.11 ▇▁▁▁▁

influence_none

Influence your ability to make impact? None of the above

Distribution

Distribution of values for influence_none

Distribution of values for influence_none

413 missing values.

Summary statistics

name label data_type n_missing complete_rate min median max mean sd hist
influence_none Influence your ability to make impact? None of the above numeric 413 0.81 0 0 1 0.03 0.18 ▇▁▁▁▁

influence_other

Influence your ability to make impact? Other

Distribution

Distribution of values for influence_other

Distribution of values for influence_other

413 missing values.

Summary statistics

name label data_type n_missing complete_rate min median max mean sd hist
influence_other Influence your ability to make impact? Other numeric 413 0.81 0 0 1 0.09 0.29 ▇▁▁▁▁

negative_80k

Negative impact on your involvement with EA so far? 80,000 Hours

Distribution

Distribution of values for negative_80k

Distribution of values for negative_80k

1026 missing values.

Summary statistics

name label data_type n_missing complete_rate min median max mean sd hist
negative_80k Negative impact on your involvement with EA so far? 80,000 Hours numeric 1026 0.53 0 0 1 0.1 0.29 ▇▁▁▁▁

negative_podcast

Negative impact on your involvement with EA so far? Podcast (not 80,000 Hours)

Distribution

Distribution of values for negative_podcast

Distribution of values for negative_podcast

1026 missing values.

Summary statistics

name label data_type n_missing complete_rate min median max mean sd hist
negative_podcast Negative impact on your involvement with EA so far? Podcast (not 80,000 Hours) numeric 1026 0.53 0 0 1 0.01 0.07 ▇▁▁▁▁

negative_givewell

Negative impact on your involvement with EA so far? GiveWell

Distribution

Distribution of values for negative_givewell

Distribution of values for negative_givewell

1026 missing values.

Summary statistics

name label data_type n_missing complete_rate min median max mean sd hist
negative_givewell Negative impact on your involvement with EA so far? GiveWell numeric 1026 0.53 0 0 1 0.01 0.08 ▇▁▁▁▁

negative_personal_contact

Negative impact on your involvement with EA so far? Personal contact with EAs

Distribution

Distribution of values for negative_personal_contact

Distribution of values for negative_personal_contact

1026 missing values.

Summary statistics

name label data_type n_missing complete_rate min median max mean sd hist
negative_personal_contact Negative impact on your involvement with EA so far? Personal contact with EAs numeric 1026 0.53 0 0 1 0.13 0.34 ▇▁▁▁▁

negative_books

Negative impact on your involvement with EA so far? Books related to EA

Distribution

Distribution of values for negative_books

Distribution of values for negative_books

1026 missing values.

Summary statistics

name label data_type n_missing complete_rate min median max mean sd hist
negative_books Negative impact on your involvement with EA so far? Books related to EA numeric 1026 0.53 0 0 1 0.01 0.1 ▇▁▁▁▁

negative_gwwc

Negative impact on your involvement with EA so far? Giving What We Can

Distribution

Distribution of values for negative_gwwc

Distribution of values for negative_gwwc

1026 missing values.

Summary statistics

name label data_type n_missing complete_rate min median max mean sd hist
negative_gwwc Negative impact on your involvement with EA so far? Giving What We Can numeric 1026 0.53 0 0 1 0.01 0.11 ▇▁▁▁▁

negative_local_group

Negative impact on your involvement with EA so far? Local EA groups

Distribution

Distribution of values for negative_local_group

Distribution of values for negative_local_group

1026 missing values.

Summary statistics

name label data_type n_missing complete_rate min median max mean sd hist
negative_local_group Negative impact on your involvement with EA so far? Local EA groups numeric 1026 0.53 0 0 1 0.07 0.25 ▇▁▁▁▁

negative_lesswrong

Negative impact on your involvement with EA so far? LessWrong

Distribution

Distribution of values for negative_lesswrong

Distribution of values for negative_lesswrong

1026 missing values.

Summary statistics

name label data_type n_missing complete_rate min median max mean sd hist
negative_lesswrong Negative impact on your involvement with EA so far? LessWrong numeric 1026 0.53 0 0 1 0.08 0.27 ▇▁▁▁▁

negative_slate_star

Negative impact on your involvement with EA so far? SlateStarCodex

Distribution

Distribution of values for negative_slate_star

Distribution of values for negative_slate_star

1026 missing values.

Summary statistics

name label data_type n_missing complete_rate min median max mean sd hist
negative_slate_star Negative impact on your involvement with EA so far? SlateStarCodex numeric 1026 0.53 0 0 1 0.03 0.18 ▇▁▁▁▁

negative_ea_global

Negative impact on your involvement with EA so far? EA Global

Distribution

Distribution of values for negative_ea_global

Distribution of values for negative_ea_global

1026 missing values.

Summary statistics

name label data_type n_missing complete_rate min median max mean sd hist
negative_ea_global Negative impact on your involvement with EA so far? EA Global numeric 1026 0.53 0 0 1 0.04 0.18 ▇▁▁▁▁

negative_eagx

Negative impact on your involvement with EA so far? EAGx

Distribution

Distribution of values for negative_eagx

Distribution of values for negative_eagx

1026 missing values.

Summary statistics

name label data_type n_missing complete_rate min median max mean sd hist
negative_eagx Negative impact on your involvement with EA so far? EAGx numeric 1026 0.53 0 0 1 0.01 0.09 ▇▁▁▁▁

negative_facebook_group

Negative impact on your involvement with EA so far? FB groups related to EA

Distribution

Distribution of values for negative_facebook_group

Distribution of values for negative_facebook_group

1026 missing values.

Summary statistics

name label data_type n_missing complete_rate min median max mean sd hist
negative_facebook_group Negative impact on your involvement with EA so far? FB groups related to EA numeric 1026 0.53 0 0 1 0.06 0.24 ▇▁▁▁▁

negative_ea_forum

Negative impact on your involvement with EA so far? The EA Forum

Distribution

Distribution of values for negative_ea_forum

Distribution of values for negative_ea_forum

1026 missing values.

Summary statistics

name label data_type n_missing complete_rate min median max mean sd hist
negative_ea_forum Negative impact on your involvement with EA so far? The EA Forum numeric 1026 0.53 0 0 1 0.07 0.25 ▇▁▁▁▁

negative_articles_blogs

Negative impact on your involvement with EA so far? Articles/blogs related EA

Distribution

Distribution of values for negative_articles_blogs

Distribution of values for negative_articles_blogs

1026 missing values.

Summary statistics

name label data_type n_missing complete_rate min median max mean sd hist
negative_articles_blogs Negative impact on your involvement with EA so far? Articles/blogs related EA numeric 1026 0.53 0 0 1 0.04 0.18 ▇▁▁▁▁

negative_ea_fellowship

Negative impact on your involvement with EA so far? An EA Fellowship

Distribution

Distribution of values for negative_ea_fellowship

Distribution of values for negative_ea_fellowship

1026 missing values.

Summary statistics

name label data_type n_missing complete_rate min median max mean sd hist
negative_ea_fellowship Negative impact on your involvement with EA so far? An EA Fellowship numeric 1026 0.53 0 0 1 0 0.06 ▇▁▁▁▁

negative_eagx2

Negative impact on your involvement with EA so far? EAGx

Distribution

Distribution of values for negative_eagx2

Distribution of values for negative_eagx2

1026 missing values.

Summary statistics

name label data_type n_missing complete_rate min median max mean sd hist
negative_eagx2 Negative impact on your involvement with EA so far? EAGx numeric 1026 0.53 0 0 1 0.01 0.07 ▇▁▁▁▁

negative_ea_newsletter

Negative impact on your involvement with EA so far? The EA Newsletter

Distribution

Distribution of values for negative_ea_newsletter

Distribution of values for negative_ea_newsletter

1026 missing values.

Summary statistics

name label data_type n_missing complete_rate min median max mean sd hist
negative_ea_newsletter Negative impact on your involvement with EA so far? The EA Newsletter numeric 1026 0.53 0 0 1 0 0.04 ▇▁▁▁▁

negative_wanbam

Negative impact on your involvement with EA so far? WANBAM

Distribution

Distribution of values for negative_wanbam

Distribution of values for negative_wanbam

1026 missing values.

Summary statistics

name label data_type n_missing complete_rate min median max mean sd hist
negative_wanbam Negative impact on your involvement with EA so far? WANBAM numeric 1026 0.53 0 0 1 0.01 0.09 ▇▁▁▁▁

negative_none

Negative impact on your involvement with EA so far? None of the above

Distribution

Distribution of values for negative_none

Distribution of values for negative_none

1026 missing values.

Summary statistics

name label data_type n_missing complete_rate min median max mean sd hist
negative_none Negative impact on your involvement with EA so far? None of the above numeric 1026 0.53 0 1 1 0.57 0.49 ▆▁▁▁▇

negative_other

Negative impact on your involvement with EA so far? Other

Distribution

Distribution of values for negative_other

Distribution of values for negative_other

1026 missing values.

Summary statistics

name label data_type n_missing complete_rate min median max mean sd hist
negative_other Negative impact on your involvement with EA so far? Other numeric 1026 0.53 0 0 1 0.09 0.28 ▇▁▁▁▁

negative_response

Negative impact on your involvement with EA so far? Open-Ended Response

Distribution

Distribution of values for negative_response

Distribution of values for negative_response

1809 missing values.

Summary statistics

name label data_type n_missing complete_rate n_unique empty min max whitespace
negative_response Negative impact on your involvement with EA so far? Open-Ended Response character 1809 0.16 349 0 2 1753 0

engaged_ea_forum

Affected your likelihood of staying engaged with EA? The EA Forum

Distribution

Distribution of values for engaged_ea_forum

Distribution of values for engaged_ea_forum

1443 missing values.

Summary statistics

name label data_type ordered value_labels n_missing complete_rate n_unique top_counts
engaged_ea_forum Affected your likelihood of staying engaged with EA? The EA Forum factor FALSE
  1. Made me a lot less likely to stay engaged,
    2. Made me less likely to stay engaged,
    3. Made me slightly less likely to stay engaged,
    4. Significant interaction, but neutral effect,
    5. Made me slightly more likely to stay engaged,
    6. Made me more likely to stay engaged,
    7. Made me a lot more likely to stay engaged
1443 0.33 7 Mad: 310, Mad: 184, Sig: 122, Mad: 44

engaged_online_community

Affected your likelihood of staying engaged with EA? The online EA community

Distribution

Distribution of values for engaged_online_community

Distribution of values for engaged_online_community

1362 missing values.

Summary statistics

name label data_type ordered value_labels n_missing complete_rate n_unique top_counts
engaged_online_community Affected your likelihood of staying engaged with EA? The online EA community factor FALSE
  1. Made me a lot less likely to stay engaged,
    2. Made me less likely to stay engaged,
    3. Made me slightly less likely to stay engaged,
    4. Significant interaction, but neutral effect,
    5. Made me slightly more likely to stay engaged,
    6. Made me more likely to stay engaged,
    7. Made me a lot more likely to stay engaged
1362 0.37 7 Mad: 342, Mad: 181, Sig: 120, Mad: 88

engaged_local_groups

Affected your likelihood of staying engaged with EA? Local EA groups

Distribution

Distribution of values for engaged_local_groups

Distribution of values for engaged_local_groups

1320 missing values.

Summary statistics

name label data_type ordered value_labels n_missing complete_rate n_unique top_counts
engaged_local_groups Affected your likelihood of staying engaged with EA? Local EA groups factor FALSE
  1. Made me a lot less likely to stay engaged,
    2. Made me less likely to stay engaged,
    3. Made me slightly less likely to stay engaged,
    4. Significant interaction, but neutral effect,
    5. Made me slightly more likely to stay engaged,
    6. Made me more likely to stay engaged,
    7. Made me a lot more likely to stay engaged
1320 0.39 7 Mad: 269, Mad: 265, Mad: 193, Sig: 68

engaged_ea_fellowship

Affected your likelihood of staying engaged with EA? An EA Fellowship

Distribution

Distribution of values for engaged_ea_fellowship

Distribution of values for engaged_ea_fellowship

1937 missing values.

Summary statistics

name label data_type ordered value_labels n_missing complete_rate n_unique top_counts
engaged_ea_fellowship Affected your likelihood of staying engaged with EA? An EA Fellowship factor FALSE
  1. Made me a lot less likely to stay engaged,
    2. Made me less likely to stay engaged,
    3. Made me slightly less likely to stay engaged,
    4. Significant interaction, but neutral effect,
    5. Made me slightly more likely to stay engaged,
    6. Made me more likely to stay engaged,
    7. Made me a lot more likely to stay engaged
1937 0.1 6 Mad: 81, Mad: 74, Mad: 43, Sig: 23

engaged_gwwc

Affected your likelihood of staying engaged with EA? Giving What We Can

Distribution

Distribution of values for engaged_gwwc

Distribution of values for engaged_gwwc

1673 missing values.

Summary statistics

name label data_type ordered value_labels n_missing complete_rate n_unique top_counts
engaged_gwwc Affected your likelihood of staying engaged with EA? Giving What We Can factor FALSE
  1. Made me a lot less likely to stay engaged,
    2. Made me less likely to stay engaged,
    3. Made me slightly less likely to stay engaged,
    4. Significant interaction, but neutral effect,
    5. Made me slightly more likely to stay engaged,
    6. Made me more likely to stay engaged,
    7. Made me a lot more likely to stay engaged
1673 0.23 7 Mad: 207, Mad: 128, Sig: 75, Mad: 64

engaged_ea_global

Affected your likelihood of staying engaged with EA? EA Global

Distribution

Distribution of values for engaged_ea_global

Distribution of values for engaged_ea_global

1790 missing values.

Summary statistics

name label data_type ordered value_labels n_missing complete_rate n_unique top_counts
engaged_ea_global Affected your likelihood of staying engaged with EA? EA Global factor FALSE
  1. Made me a lot less likely to stay engaged,
    2. Made me less likely to stay engaged,
    3. Made me slightly less likely to stay engaged,
    4. Significant interaction, but neutral effect,
    5. Made me slightly more likely to stay engaged,
    6. Made me more likely to stay engaged,
    7. Made me a lot more likely to stay engaged
1790 0.17 7 Mad: 138, Mad: 87, Sig: 66, Mad: 63

engaged_eagx

Affected your likelihood of staying engaged with EA? EAGx

Distribution

Distribution of values for engaged_eagx

Distribution of values for engaged_eagx

1775 missing values.

Summary statistics

name label data_type ordered value_labels n_missing complete_rate n_unique top_counts
engaged_eagx Affected your likelihood of staying engaged with EA? EAGx factor FALSE
  1. Made me a lot less likely to stay engaged,
    2. Made me less likely to stay engaged,
    3. Made me slightly less likely to stay engaged,
    4. Significant interaction, but neutral effect,
    5. Made me slightly more likely to stay engaged,
    6. Made me more likely to stay engaged,
    7. Made me a lot more likely to stay engaged
1775 0.18 7 Mad: 139, Mad: 104, Sig: 67, Mad: 65

engaged_ea_newsletter

Affected your likelihood of staying engaged with EA? The EA Newsletter

Distribution

Distribution of values for engaged_ea_newsletter

Distribution of values for engaged_ea_newsletter

1528 missing values.

Summary statistics

name label data_type ordered value_labels n_missing complete_rate n_unique top_counts
engaged_ea_newsletter Affected your likelihood of staying engaged with EA? The EA Newsletter factor FALSE
  1. Made me a lot less likely to stay engaged,
    2. Made me less likely to stay engaged,
    3. Made me slightly less likely to stay engaged,
    4. Significant interaction, but neutral effect,
    5. Made me slightly more likely to stay engaged,
    6. Made me more likely to stay engaged,
    7. Made me a lot more likely to stay engaged
1528 0.29 7 Mad: 310, Sig: 172, Mad: 113, Mad: 22

engaged_wanbam

Affected your likelihood of staying engaged with EA? WANBAM

Distribution

Distribution of values for engaged_wanbam

Distribution of values for engaged_wanbam

2055 missing values.

Summary statistics

name label data_type ordered value_labels n_missing complete_rate n_unique top_counts
engaged_wanbam Affected your likelihood of staying engaged with EA? WANBAM factor FALSE
  1. Made me a lot less likely to stay engaged,
    2. Made me less likely to stay engaged,
    3. Made me slightly less likely to stay engaged,
    4. Significant interaction, but neutral effect,
    5. Made me slightly more likely to stay engaged,
    6. Made me more likely to stay engaged,
    7. Made me a lot more likely to stay engaged
2055 0.05 7 Mad: 29, Sig: 26, Mad: 21, Mad: 19

engaged_personal_contact

Affected your likelihood of staying engaged with EA? Personal contacts

Distribution

Distribution of values for engaged_personal_contact

Distribution of values for engaged_personal_contact

1068 missing values.

Summary statistics

name label data_type ordered value_labels n_missing complete_rate n_unique top_counts
engaged_personal_contact Affected your likelihood of staying engaged with EA? Personal contacts factor FALSE
  1. Made me a lot less likely to stay engaged,
    2. Made me less likely to stay engaged,
    3. Made me slightly less likely to stay engaged,
    4. Significant interaction, but neutral effect,
    5. Made me slightly more likely to stay engaged,
    6. Made me more likely to stay engaged,
    7. Made me a lot more likely to stay engaged
1068 0.51 7 Mad: 380, Mad: 356, Mad: 251, Sig: 74

engaged_80k_podcast

Affected your likelihood of staying engaged with EA? 80,000 Hours (podcast)

Distribution

Distribution of values for engaged_80k_podcast

Distribution of values for engaged_80k_podcast

1298 missing values.

Summary statistics

name label data_type ordered value_labels n_missing complete_rate n_unique top_counts
engaged_80k_podcast Affected your likelihood of staying engaged with EA? 80,000 Hours (podcast) factor FALSE
  1. Made me a lot less likely to stay engaged,
    2. Made me less likely to stay engaged,
    3. Made me slightly less likely to stay engaged,
    4. Significant interaction, but neutral effect,
    5. Made me slightly more likely to stay engaged,
    6. Made me more likely to stay engaged,
    7. Made me a lot more likely to stay engaged
1298 0.4 7 Mad: 371, Mad: 223, Sig: 139, Mad: 97

engaged_80k_hours

Affected your likelihood of staying engaged with EA? 80,000 Hours (website)

Distribution

Distribution of values for engaged_80k_hours

Distribution of values for engaged_80k_hours

1234 missing values.

Summary statistics

name label data_type ordered value_labels n_missing complete_rate n_unique top_counts
engaged_80k_hours Affected your likelihood of staying engaged with EA? 80,000 Hours (website) factor FALSE
  1. Made me a lot less likely to stay engaged,
    2. Made me less likely to stay engaged,
    3. Made me slightly less likely to stay engaged,
    4. Significant interaction, but neutral effect,
    5. Made me slightly more likely to stay engaged,
    6. Made me more likely to stay engaged,
    7. Made me a lot more likely to stay engaged
1234 0.43 7 Mad: 396, Mad: 230, Sig: 139, Mad: 111

engaged_80k_one_on_one

Affected your likelihood of staying engaged with EA? 80k Hours (1-on-1 career)

Distribution

Distribution of values for engaged_80k_one_on_one

Distribution of values for engaged_80k_one_on_one

2045 missing values.

Summary statistics

name label data_type ordered value_labels n_missing complete_rate n_unique top_counts
engaged_80k_one_on_one Affected your likelihood of staying engaged with EA? 80k Hours (1-on-1 career) factor FALSE
  1. Made me a lot less likely to stay engaged,
    2. Made me less likely to stay engaged,
    3. Made me slightly less likely to stay engaged,
    4. Significant interaction, but neutral effect,
    5. Made me slightly more likely to stay engaged,
    6. Made me more likely to stay engaged,
    7. Made me a lot more likely to stay engaged
2045 0.05 7 Mad: 35, Mad: 25, Sig: 24, Mad: 20

engaged_givewell

Affected your likelihood of staying engaged with EA? GiveWell

Distribution

Distribution of values for engaged_givewell

Distribution of values for engaged_givewell

1410 missing values.

Summary statistics

name label data_type ordered value_labels n_missing complete_rate n_unique top_counts
engaged_givewell Affected your likelihood of staying engaged with EA? GiveWell factor FALSE
  1. Made me a lot less likely to stay engaged,
    2. Made me less likely to stay engaged,
    3. Made me slightly less likely to stay engaged,
    4. Significant interaction, but neutral effect,
    5. Made me slightly more likely to stay engaged,
    6. Made me more likely to stay engaged,
    7. Made me a lot more likely to stay engaged
1410 0.35 7 Mad: 311, Mad: 244, Sig: 89, Mad: 87

engaged_lesswrong

Affected your likelihood of staying engaged with EA? LessWrong

Distribution

Distribution of values for engaged_lesswrong

Distribution of values for engaged_lesswrong

1601 missing values.

Summary statistics

name label data_type ordered value_labels n_missing complete_rate n_unique top_counts
engaged_lesswrong Affected your likelihood of staying engaged with EA? LessWrong factor FALSE
  1. Made me a lot less likely to stay engaged,
    2. Made me less likely to stay engaged,
    3. Made me slightly less likely to stay engaged,
    4. Significant interaction, but neutral effect,
    5. Made me slightly more likely to stay engaged,
    6. Made me more likely to stay engaged,
    7. Made me a lot more likely to stay engaged
1601 0.26 7 Mad: 205, Sig: 153, Mad: 94, Mad: 50

engaged_slate_star

Affected your likelihood of staying engaged with EA? Slate Star Codex

Distribution

Distribution of values for engaged_slate_star

Distribution of values for engaged_slate_star

1589 missing values.

Summary statistics

name label data_type ordered value_labels n_missing complete_rate n_unique top_counts
engaged_slate_star Affected your likelihood of staying engaged with EA? Slate Star Codex factor FALSE
  1. Made me a lot less likely to stay engaged,
    2. Made me less likely to stay engaged,
    3. Made me slightly less likely to stay engaged,
    4. Significant interaction, but neutral effect,
    5. Made me slightly more likely to stay engaged,
    6. Made me more likely to stay engaged,
    7. Made me a lot more likely to stay engaged
1589 0.27 7 Mad: 198, Sig: 186, Mad: 112, Mad: 30

substantial_affect_impact

Are there other things which have substantially affected your impact?

Distribution

Distribution of values for substantial_affect_impact

Distribution of values for substantial_affect_impact

1699 missing values.

Summary statistics

name label data_type n_missing complete_rate n_unique empty min max whitespace
substantial_affect_impact Are there other things which have substantially affected your impact? character 1699 0.21 454 0 2 2642 0

prioritize_animal_welfare

Distribution

Distribution of values for prioritize_animal_welfare

Distribution of values for prioritize_animal_welfare

561 missing values.

Summary statistics

name data_type ordered value_labels n_missing complete_rate n_unique top_counts label
prioritize_animal_welfare factor FALSE
  1. 1,
    2. 2,
    3. 3,
    4. 4,
    5. 5
561 0.74 5 3: 576, 4: 455, 2: 316, 5: 158 NA

prioritize_causes

Distribution

Distribution of values for prioritize_causes

Distribution of values for prioritize_causes

689 missing values.

Summary statistics

name data_type ordered value_labels n_missing complete_rate n_unique top_counts label
prioritize_causes factor FALSE
  1. 1,
    2. 2,
    3. 3,
    4. 4,
    5. 5
689 0.68 5 4: 509, 3: 434, 5: 278, 2: 228 NA

prioritize_climate_change

Distribution

Distribution of values for prioritize_climate_change

Distribution of values for prioritize_climate_change

561 missing values.

Summary statistics

name data_type ordered value_labels n_missing complete_rate n_unique top_counts label
prioritize_climate_change factor FALSE
  1. 1,
    2. 2,
    3. 3,
    4. 4,
    5. 5
561 0.74 5 3: 433, 4: 432, 2: 339, 5: 307 NA

prioritize_biosecurity

Distribution

Distribution of values for prioritize_biosecurity

Distribution of values for prioritize_biosecurity

583 missing values.

Summary statistics

name data_type ordered value_labels n_missing complete_rate n_unique top_counts label
prioritize_biosecurity factor FALSE
  1. 1,
    2. 2,
    3. 3,
    4. 4,
    5. 5
583 0.73 5 4: 657, 3: 532, 2: 224, 5: 136 NA

prioritize_nuclear_security

Distribution

Distribution of values for prioritize_nuclear_security

Distribution of values for prioritize_nuclear_security

652 missing values.

Summary statistics

name data_type ordered value_labels n_missing complete_rate n_unique top_counts label
prioritize_nuclear_security factor FALSE
  1. 1,
    2. 2,
    3. 3,
    4. 4,
    5. 5
652 0.7 5 3: 593, 2: 385, 4: 369, 5: 92 NA

prioritize_ai_risks

Distribution

Distribution of values for prioritize_ai_risks

Distribution of values for prioritize_ai_risks

601 missing values.

Summary statistics

name data_type ordered value_labels n_missing complete_rate n_unique top_counts label
prioritize_ai_risks factor FALSE
  1. 1,
    2. 2,
    3. 3,
    4. 4,
    5. 5
601 0.72 5 4: 560, 3: 395, 5: 311, 2: 229 NA

prioritize_mental_health

Distribution

Distribution of values for prioritize_mental_health

Distribution of values for prioritize_mental_health

641 missing values.

Summary statistics

name data_type ordered value_labels n_missing complete_rate n_unique top_counts label
prioritize_mental_health factor FALSE
  1. 1,
    2. 2,
    3. 3,
    4. 4,
    5. 5
641 0.7 5 3: 549, 2: 489, 4: 287, 1: 118 NA

prioritize_global_poverty

Distribution

Distribution of values for prioritize_global_poverty

Distribution of values for prioritize_global_poverty

539 missing values.

Summary statistics

name data_type ordered value_labels n_missing complete_rate n_unique top_counts label
prioritize_global_poverty factor FALSE
  1. 1,
    2. 2,
    3. 3,
    4. 4,
    5. 5
539 0.75 5 4: 603, 3: 412, 5: 374, 2: 208 NA

prioritize_meta

Distribution

Distribution of values for prioritize_meta

Distribution of values for prioritize_meta

1107 missing values.

Summary statistics

name data_type ordered value_labels n_missing complete_rate n_unique top_counts label
prioritize_meta factor FALSE
  1. 1,
    2. 2,
    3. 3,
    4. 4,
    5. 5
1107 0.49 5 3: 366, 2: 363, 4: 206, 5: 62 NA

prioritize_ea_movement

Distribution

Distribution of values for prioritize_ea_movement

Distribution of values for prioritize_ea_movement

639 missing values.

Summary statistics

name data_type ordered value_labels n_missing complete_rate n_unique top_counts label
prioritize_ea_movement factor FALSE
  1. 1,
    2. 2,
    3. 3,
    4. 4,
    5. 5
639 0.7 5 3: 558, 4: 469, 2: 308, 5: 164 NA

prioritize_x_risks

Distribution

Distribution of values for prioritize_x_risks

Distribution of values for prioritize_x_risks

678 missing values.

Summary statistics

name data_type ordered value_labels n_missing complete_rate n_unique top_counts label
prioritize_x_risks factor FALSE
  1. 1,
    2. 2,
    3. 3,
    4. 4,
    5. 5
678 0.69 5 3: 504, 4: 484, 2: 280, 5: 164 NA

prioritize_broad_longtermism

Distribution

Distribution of values for prioritize_broad_longtermism

Distribution of values for prioritize_broad_longtermism

758 missing values.

Summary statistics

name data_type ordered value_labels n_missing complete_rate n_unique top_counts label
prioritize_broad_longtermism factor FALSE
  1. 1,
    2. 2,
    3. 3,
    4. 4,
    5. 5
758 0.65 5 3: 445, 4: 390, 2: 359, 5: 142 NA

prioritize_other

Are there any other causes you feel should be priorities for the EA community?

Distribution

Distribution of values for prioritize_other

Distribution of values for prioritize_other

1697 missing values.

Summary statistics

name label data_type n_missing complete_rate n_unique empty min max whitespace
prioritize_other Are there any other causes you feel should be priorities for the EA community? character 1697 0.22 458 0 2 608 0

currency

Distribution

Distribution of values for currency

Distribution of values for currency

555 missing values.

Summary statistics

name data_type n_missing complete_rate n_unique empty min max whitespace label
currency character 555 0.74 22 0 3 3 0 NA

currency_other

Please select the currency that pertains to you. Other

Distribution

Distribution of values for currency_other

Distribution of values for currency_other

0 missing values.

Summary statistics

name label data_type n_missing complete_rate n_unique empty min max whitespace
currency_other Please select the currency that pertains to you. Other character 0 1 94 1961 0 37 0

income

What was your pre-tax individual income in 2019?

Distribution

Distribution of values for income

Distribution of values for income

665 missing values.

Summary statistics

name label data_type n_missing complete_rate min median max mean sd hist
income What was your pre-tax individual income in 2019? numeric 665 0.69 0 35000 36000000 151598 1104476 ▇▁▁▁▁

donation_2019

In 2019, roughly how much money did you donate?

Distribution

Distribution of values for donation_2019

Distribution of values for donation_2019

647 missing values.

Summary statistics

name label data_type n_missing complete_rate min median max mean sd hist
donation_2019 In 2019, roughly how much money did you donate? numeric 647 0.7 0 600 3e+06 12315 109658 ▇▁▁▁▁

donation_2020

In 2020, how much do you currently plan to donate?

Distribution

Distribution of values for donation_2020

Distribution of values for donation_2020

669 missing values.

Summary statistics

name label data_type n_missing complete_rate min median max mean sd hist
donation_2020 In 2020, how much do you currently plan to donate? numeric 669 0.69 0 1200 3e+06 15640 113144 ▇▁▁▁▁

university_original

If applicable, which university or universities did you attend?

Distribution

Distribution of values for university_original

Distribution of values for university_original

712 missing values.

Summary statistics

name label data_type n_missing complete_rate n_unique empty min max whitespace
university_original If applicable, which university or universities did you attend? character 712 0.67 1079 0 1 141 0

birth_year

In which year were you born?

Distribution

Distribution of values for birth_year

Distribution of values for birth_year

505 missing values.

Summary statistics

name label data_type n_missing complete_rate min median max mean sd hist
birth_year In which year were you born? numeric 505 0.77 1918 1993 2016 1990 9.8 ▁▁▁▇▃

gender_original

Gender, original

Distribution

Distribution of values for gender_original

Distribution of values for gender_original

526 missing values.

Summary statistics

name label data_type n_missing complete_rate n_unique empty min max whitespace
gender_original Gender, original character 526 0.76 88 0 1 82 0

sexual_orientation

What is your sexual orientation?

Distribution

Distribution of values for sexual_orientation

Distribution of values for sexual_orientation

686 missing values.

Summary statistics

name label data_type n_missing complete_rate n_unique empty min max whitespace
sexual_orientation What is your sexual orientation? character 686 0.68 166 0 1 123 0

country

Distribution

Distribution of values for country

Distribution of values for country

0 missing values.

Summary statistics

name data_type n_missing complete_rate n_unique empty min max whitespace label
country character 0 1 62 503 0 24 0 NA

city_other

In what town/city/metropolitan area do you live? Other

Distribution

Distribution of values for city_other

Distribution of values for city_other

1296 missing values.

Summary statistics

name label data_type n_missing complete_rate n_unique empty min max whitespace
city_other In what town/city/metropolitan area do you live? Other character 1296 0.4 465 0 2 88 0

ea_community_ideal

How well does the EA community compare to your ideal?

Distribution

Distribution of values for ea_community_ideal

Distribution of values for ea_community_ideal

617 missing values.

Summary statistics

name label data_type n_missing complete_rate min median max mean sd hist
ea_community_ideal How well does the EA community compare to your ideal? numeric 617 0.71 1 7 10 7 1.7 ▁▁▃▇▂

ea_community_satisfaction

What is your overall satisfaction with the EA community?

Distribution

Distribution of values for ea_community_satisfaction

Distribution of values for ea_community_satisfaction

624 missing values.

Summary statistics

name label data_type n_missing complete_rate min median max mean sd hist
ea_community_satisfaction What is your overall satisfaction with the EA community? numeric 624 0.71 1 8 10 7.3 1.7 ▁▁▃▇▃

ea_community_why

Why did you give the two ratings above? Open-Ended Response

Distribution

Distribution of values for ea_community_why

Distribution of values for ea_community_why

1101 missing values.

Summary statistics

name label data_type n_missing complete_rate n_unique empty min max whitespace
ea_community_why Why did you give the two ratings above? Open-Ended Response character 1101 0.49 1062 0 6 2291 0

agree_ea_helps_impact

Agree: The EA community helps me have more impact.

Distribution

Distribution of values for agree_ea_helps_impact

Distribution of values for agree_ea_helps_impact

603 missing values.

Summary statistics

name label data_type ordered value_labels n_missing complete_rate n_unique top_counts
agree_ea_helps_impact Agree: The EA community helps me have more impact. factor FALSE
    1. Strongly disagree,
      2. (2) Disagree,
      3. (3) Neither agree nor disagree,
      4. (4) Agree,
      5. (5) Strongly agree
603 0.72 5 (4): 634, (3): 413, (5): 355, (2): 105

agree_part_of_ea_community

Agree: I feel that I am a part of the effective altruism community.

Distribution

Distribution of values for agree_part_of_ea_community

Distribution of values for agree_part_of_ea_community

584 missing values.

Summary statistics

name label data_type ordered value_labels n_missing complete_rate n_unique top_counts
agree_part_of_ea_community Agree: I feel that I am a part of the effective altruism community. factor FALSE
    1. Strongly disagree,
      2. (2) Disagree,
      3. (3) Neither agree nor disagree,
      4. (4) Agree,
      5. (5) Strongly agree
584 0.73 5 (4): 621, (5): 353, (3): 334, (2): 214

friend_introduce

How excited would you be to introduce a friend to the EA community?

Distribution

Distribution of values for friend_introduce

Distribution of values for friend_introduce

581 missing values.

Summary statistics

name label data_type n_missing complete_rate min median max mean sd hist
friend_introduce How excited would you be to introduce a friend to the EA community? numeric 581 0.73 1 8 10 7.7 2 ▁▁▃▇▇

learned_80k

80,000 Hours - Changed mind or learned something important

Distribution

Distribution of values for learned_80k

Distribution of values for learned_80k

829 missing values.

Summary statistics

name label data_type n_missing complete_rate min median max mean sd hist
learned_80k 80,000 Hours - Changed mind or learned something important numeric 829 0.62 0 0 1 0.39 0.49 ▇▁▁▁▅

connection_80k

80,000 Hours - New interesting and valuable connection

Distribution

Distribution of values for connection_80k

Distribution of values for connection_80k

829 missing values.

Summary statistics

name label data_type n_missing complete_rate min median max mean sd hist
connection_80k 80,000 Hours - New interesting and valuable connection numeric 829 0.62 0 0 1 0.09 0.28 ▇▁▁▁▁

learned_ea_global

EA Global - Changed mind or learned something important

Distribution

Distribution of values for learned_ea_global

Distribution of values for learned_ea_global

829 missing values.

Summary statistics

name label data_type n_missing complete_rate min median max mean sd hist
learned_ea_global EA Global - Changed mind or learned something important numeric 829 0.62 0 0 1 0.07 0.25 ▇▁▁▁▁

connection_ea_global

EA Global - New interesting and valuable connection

Distribution

Distribution of values for connection_ea_global

Distribution of values for connection_ea_global

829 missing values.

Summary statistics

name label data_type n_missing complete_rate min median max mean sd hist
connection_ea_global EA Global - New interesting and valuable connection numeric 829 0.62 0 0 1 0.11 0.31 ▇▁▁▁▁

learned_ea_hub

EA Hub - Changed mind or learned something important

Distribution

Distribution of values for learned_ea_hub

Distribution of values for learned_ea_hub

829 missing values.

Summary statistics

name label data_type n_missing complete_rate min median max mean sd hist
learned_ea_hub EA Hub - Changed mind or learned something important numeric 829 0.62 0 0 1 0.02 0.14 ▇▁▁▁▁

connection_ea_hub

EA Hub - New interesting and valuable connection

Distribution

Distribution of values for connection_ea_hub

Distribution of values for connection_ea_hub

829 missing values.

Summary statistics

name label data_type n_missing complete_rate min median max mean sd hist
connection_ea_hub EA Hub - New interesting and valuable connection numeric 829 0.62 0 0 1 0.02 0.14 ▇▁▁▁▁

learned_ea_student_mentoring

EA Student Career Mentoring - Changed mind or learned something important

Distribution

Distribution of values for learned_ea_student_mentoring

Distribution of values for learned_ea_student_mentoring

829 missing values.

Summary statistics

name label data_type n_missing complete_rate min median max mean sd hist
learned_ea_student_mentoring EA Student Career Mentoring - Changed mind or learned something important numeric 829 0.62 0 0 1 0.03 0.16 ▇▁▁▁▁

connection_ea_student_mentor

EA Student Career Mentoring - New interesting and valuable connection

Distribution

Distribution of values for connection_ea_student_mentor

Distribution of values for connection_ea_student_mentor

829 missing values.

Summary statistics

name label data_type n_missing complete_rate min median max mean sd hist
connection_ea_student_mentor EA Student Career Mentoring - New interesting and valuable connection numeric 829 0.62 0 0 1 0.03 0.18 ▇▁▁▁▁

learned_eagx

EAGx - Changed mind or learned something important

Distribution

Distribution of values for learned_eagx

Distribution of values for learned_eagx

829 missing values.

Summary statistics

name label data_type n_missing complete_rate min median max mean sd hist
learned_eagx EAGx - Changed mind or learned something important numeric 829 0.62 0 0 1 0.07 0.26 ▇▁▁▁▁

connection_eagx

EAGx - New interesting and valuable connection

Distribution

Distribution of values for connection_eagx

Distribution of values for connection_eagx

829 missing values.

Summary statistics

name label data_type n_missing complete_rate min median max mean sd hist
connection_eagx EAGx - New interesting and valuable connection numeric 829 0.62 0 0 1 0.11 0.32 ▇▁▁▁▁

learned_effective_thesis

Effective Thesis - Changed mind or learned something important

Distribution

Distribution of values for learned_effective_thesis

Distribution of values for learned_effective_thesis

829 missing values.

Summary statistics

name label data_type n_missing complete_rate min median max mean sd hist
learned_effective_thesis Effective Thesis - Changed mind or learned something important numeric 829 0.62 0 0 1 0.02 0.15 ▇▁▁▁▁

connection_effective_thesis

Effective Thesis - New interesting and valuable connection

Distribution

Distribution of values for connection_effective_thesis

Distribution of values for connection_effective_thesis

829 missing values.

Summary statistics

name label data_type n_missing complete_rate min median max mean sd hist
connection_effective_thesis Effective Thesis - New interesting and valuable connection numeric 829 0.62 0 0 1 0.03 0.16 ▇▁▁▁▁

learned_facebook_group

Facebook groups related to EA - Changed mind or learned something important

Distribution

Distribution of values for learned_facebook_group

Distribution of values for learned_facebook_group

829 missing values.

Summary statistics

name label data_type n_missing complete_rate min median max mean sd hist
learned_facebook_group Facebook groups related to EA - Changed mind or learned something important numeric 829 0.62 0 0 1 0.09 0.28 ▇▁▁▁▁

connection_facebook_group

Facebook groups related to EA - New interesting and valuable connection

Distribution

Distribution of values for connection_facebook_group

Distribution of values for connection_facebook_group

829 missing values.

Summary statistics

name label data_type n_missing complete_rate min median max mean sd hist
connection_facebook_group Facebook groups related to EA - New interesting and valuable connection numeric 829 0.62 0 0 1 0.09 0.28 ▇▁▁▁▁

learned_gwwc

Giving What We Can - Changed mind or learned something important

Distribution

Distribution of values for learned_gwwc

Distribution of values for learned_gwwc

829 missing values.

Summary statistics

name label data_type n_missing complete_rate min median max mean sd hist
learned_gwwc Giving What We Can - Changed mind or learned something important numeric 829 0.62 0 0 1 0.07 0.25 ▇▁▁▁▁

connection_gwwc

Giving What We Can - New interesting and valuable connection

Distribution

Distribution of values for connection_gwwc

Distribution of values for connection_gwwc

829 missing values.

Summary statistics

name label data_type n_missing complete_rate min median max mean sd hist
connection_gwwc Giving What We Can - New interesting and valuable connection numeric 829 0.62 0 0 1 0.05 0.21 ▇▁▁▁▁

learned_intl_ea_events

International EA social events - Changed mind or learned something important

Distribution

Distribution of values for learned_intl_ea_events

Distribution of values for learned_intl_ea_events

829 missing values.

Summary statistics

name label data_type n_missing complete_rate min median max mean sd hist
learned_intl_ea_events International EA social events - Changed mind or learned something important numeric 829 0.62 0 0 1 0.04 0.21 ▇▁▁▁▁

connection_intl_ea_events

International EA social events - New interesting and valuable connection

Distribution

Distribution of values for connection_intl_ea_events

Distribution of values for connection_intl_ea_events

829 missing values.

Summary statistics

name label data_type n_missing complete_rate min median max mean sd hist
connection_intl_ea_events International EA social events - New interesting and valuable connection numeric 829 0.62 0 0 1 0.09 0.28 ▇▁▁▁▁

learned_personal_connection

A personal connection - Changed mind or learned something important

Distribution

Distribution of values for learned_personal_connection

Distribution of values for learned_personal_connection

829 missing values.

Summary statistics

name label data_type n_missing complete_rate min median max mean sd hist
learned_personal_connection A personal connection - Changed mind or learned something important numeric 829 0.62 0 0 1 0.27 0.44 ▇▁▁▁▃

connection_personal_contact

A personal connection - New interesting and valuable connection

Distribution

Distribution of values for connection_personal_contact

Distribution of values for connection_personal_contact

829 missing values.

Summary statistics

name label data_type n_missing complete_rate min median max mean sd hist
connection_personal_contact A personal connection - New interesting and valuable connection numeric 829 0.62 0 0 1 0.27 0.45 ▇▁▁▁▃

learned_lesswrong

LessWrong - Changed mind or learned something important

Distribution

Distribution of values for learned_lesswrong

Distribution of values for learned_lesswrong

829 missing values.

Summary statistics

name label data_type n_missing complete_rate min median max mean sd hist
learned_lesswrong LessWrong - Changed mind or learned something important numeric 829 0.62 0 0 1 0.14 0.35 ▇▁▁▁▂

connection_lesswrong

LessWrong - New interesting and valuable connection

Distribution

Distribution of values for connection_lesswrong

Distribution of values for connection_lesswrong

829 missing values.

Summary statistics

name label data_type n_missing complete_rate min median max mean sd hist
connection_lesswrong LessWrong - New interesting and valuable connection numeric 829 0.62 0 0 1 0.05 0.22 ▇▁▁▁▁

learned_local_group

Local EA groups - Changed mind or learned something important

Distribution

Distribution of values for learned_local_group

Distribution of values for learned_local_group

829 missing values.

Summary statistics

name label data_type n_missing complete_rate min median max mean sd hist
learned_local_group Local EA groups - Changed mind or learned something important numeric 829 0.62 0 0 1 0.17 0.38 ▇▁▁▁▂

connection_local_groups

Local EA groups - New interesting and valuable connection

Distribution

Distribution of values for connection_local_groups

Distribution of values for connection_local_groups

829 missing values.

Summary statistics

name label data_type n_missing complete_rate min median max mean sd hist
connection_local_groups Local EA groups - New interesting and valuable connection numeric 829 0.62 0 0 1 0.27 0.45 ▇▁▁▁▃

learned_non_local_group

Non-local meetups - Changed mind or learned something important

Distribution

Distribution of values for learned_non_local_group

Distribution of values for learned_non_local_group

829 missing values.

Summary statistics

name label data_type n_missing complete_rate min median max mean sd hist
learned_non_local_group Non-local meetups - Changed mind or learned something important numeric 829 0.62 0 0 1 0.02 0.16 ▇▁▁▁▁

connection_non_local_group

Non-local meetups - New interesting and valuable connection

Distribution

Distribution of values for connection_non_local_group

Distribution of values for connection_non_local_group

829 missing values.

Summary statistics

name label data_type n_missing complete_rate min median max mean sd hist
connection_non_local_group Non-local meetups - New interesting and valuable connection numeric 829 0.62 0 0 1 0.05 0.22 ▇▁▁▁▁

learned_ea_forum

The EA Forum - Changed mind or learned something important

Distribution

Distribution of values for learned_ea_forum

Distribution of values for learned_ea_forum

829 missing values.

Summary statistics

name label data_type n_missing complete_rate min median max mean sd hist
learned_ea_forum The EA Forum - Changed mind or learned something important numeric 829 0.62 0 0 1 0.19 0.4 ▇▁▁▁▂

connection_ea_forum

The EA Forum - New interesting and valuable connection

Distribution

Distribution of values for connection_ea_forum

Distribution of values for connection_ea_forum

829 missing values.

Summary statistics

name label data_type n_missing complete_rate min median max mean sd hist
connection_ea_forum The EA Forum - New interesting and valuable connection numeric 829 0.62 0 0 1 0.06 0.23 ▇▁▁▁▁

learned_ea_books

EA books - Changed mind or learned something important

Distribution

Distribution of values for learned_ea_books

Distribution of values for learned_ea_books

829 missing values.

Summary statistics

name label data_type n_missing complete_rate min median max mean sd hist
learned_ea_books EA books - Changed mind or learned something important numeric 829 0.62 0 0 1 0.24 0.43 ▇▁▁▁▂

connection_ea_books

EA books - New interesting and valuable connection

Distribution

Distribution of values for connection_ea_books

Distribution of values for connection_ea_books

829 missing values.

Summary statistics

name label data_type n_missing complete_rate min median max mean sd hist
connection_ea_books EA books - New interesting and valuable connection numeric 829 0.62 0 0 1 0.05 0.23 ▇▁▁▁▁

learned_ea_newsletter

The EA Newsletter - Changed mind or learned something important

Distribution

Distribution of values for learned_ea_newsletter

Distribution of values for learned_ea_newsletter

829 missing values.

Summary statistics

name label data_type n_missing complete_rate min median max mean sd hist
learned_ea_newsletter The EA Newsletter - Changed mind or learned something important numeric 829 0.62 0 0 1 0.09 0.29 ▇▁▁▁▁

connection_ea_newsletter

The EA Newsletter - New interesting and valuable connection

Distribution

Distribution of values for connection_ea_newsletter

Distribution of values for connection_ea_newsletter

829 missing values.

Summary statistics

name label data_type n_missing complete_rate min median max mean sd hist
connection_ea_newsletter The EA Newsletter - New interesting and valuable connection numeric 829 0.62 0 0 1 0.04 0.2 ▇▁▁▁▁

learned_none

None of the above - Changed mind or learned something important

Distribution

Distribution of values for learned_none

Distribution of values for learned_none

829 missing values.

Summary statistics

name label data_type n_missing complete_rate min median max mean sd hist
learned_none None of the above - Changed mind or learned something important numeric 829 0.62 0 0 1 0.08 0.28 ▇▁▁▁▁

connection_none

None of the above - New interesting and valuable connection

Distribution

Distribution of values for connection_none

Distribution of values for connection_none

829 missing values.

Summary statistics

name label data_type n_missing complete_rate min median max mean sd hist
connection_none None of the above - New interesting and valuable connection numeric 829 0.62 0 0 1 0.09 0.29 ▇▁▁▁▁

learned_connection_other

Other (please specify)

Distribution

Distribution of values for learned_connection_other

Distribution of values for learned_connection_other

829 missing values.

Summary statistics

name label data_type n_missing complete_rate min median max mean sd hist
learned_connection_other Other (please specify) numeric 829 0.62 0 0 1 0.08 0.28 ▇▁▁▁▁

participate_doing_good_better

Interested in: A reading group to discuss Doing Good Better

Distribution

Distribution of values for participate_doing_good_better

Distribution of values for participate_doing_good_better

1941 missing values.

Summary statistics

name label data_type n_missing complete_rate min median max mean sd hist
participate_doing_good_better Interested in: A reading group to discuss Doing Good Better numeric 1941 0.1 1 1 1 1 0 ▁▁▇▁▁

participate_the_precipice

Interested in: A reading group to discuss The Precipice

Distribution

Distribution of values for participate_the_precipice

Distribution of values for participate_the_precipice

1847 missing values.

Summary statistics

name label data_type n_missing complete_rate min median max mean sd hist
participate_the_precipice Interested in: A reading group to discuss The Precipice numeric 1847 0.15 1 1 1 1 0 ▁▁▇▁▁

participate_fellowship_intro

Interested in: A fellowship covering the basics of effective altruism

Distribution

Distribution of values for participate_fellowship_intro

Distribution of values for participate_fellowship_intro

1973 missing values.

Summary statistics

name label data_type n_missing complete_rate min median max mean sd hist
participate_fellowship_intro Interested in: A fellowship covering the basics of effective altruism numeric 1973 0.09 1 1 1 1 0 ▁▁▇▁▁

participate_fellowship_adv

Interested in: A fellowship covering advanced principles of effective altruism

Distribution

Distribution of values for participate_fellowship_adv

Distribution of values for participate_fellowship_adv

1702 missing values.

Summary statistics

name label data_type n_missing complete_rate min median max mean sd hist
participate_fellowship_adv Interested in: A fellowship covering advanced principles of effective altruism numeric 1702 0.21 1 1 1 1 0 ▁▁▇▁▁

participate_80k_pod_discuss

Interested in: An 80,000 Hours podcast discussion group

Distribution

Distribution of values for participate_80k_pod_discuss

Distribution of values for participate_80k_pod_discuss

1901 missing values.

Summary statistics

name label data_type n_missing complete_rate min median max mean sd hist
participate_80k_pod_discuss Interested in: An 80,000 Hours podcast discussion group numeric 1901 0.12 1 1 1 1 0 ▁▁▇▁▁

participate_fellowship_career

Interested in: A 4-part fellowship using the 80k tool for career planning

Distribution

Distribution of values for participate_fellowship_career

Distribution of values for participate_fellowship_career

1735 missing values.

Summary statistics

name label data_type n_missing complete_rate min median max mean sd hist
participate_fellowship_career Interested in: A 4-part fellowship using the 80k tool for career planning numeric 1735 0.2 1 1 1 1 0 ▁▁▇▁▁

participate_fellowship_causes

Interested in: A fellowship covering key ideas related to your top cause area

Distribution

Distribution of values for participate_fellowship_causes

Distribution of values for participate_fellowship_causes

1694 missing values.

Summary statistics

name label data_type n_missing complete_rate min median max mean sd hist
participate_fellowship_causes Interested in: A fellowship covering key ideas related to your top cause area numeric 1694 0.22 1 1 1 1 0 ▁▁▇▁▁

participate_intro_one_on_one

Interested in: An introductory 1-on-1 convo to discuss the basic ideas of EA

Distribution

Distribution of values for participate_intro_one_on_one

Distribution of values for participate_intro_one_on_one

2030 missing values.

Summary statistics

name label data_type n_missing complete_rate min median max mean sd hist
participate_intro_one_on_one Interested in: An introductory 1-on-1 convo to discuss the basic ideas of EA numeric 2030 0.06 1 1 1 1 0 ▁▁▇▁▁

participate_gwwc_info_session

Interested in: A one-time information session about GWWC / Try Giving

Distribution

Distribution of values for participate_gwwc_info_session

Distribution of values for participate_gwwc_info_session

2019 missing values.

Summary statistics

name label data_type n_missing complete_rate min median max mean sd hist
participate_gwwc_info_session Interested in: A one-time information session about GWWC / Try Giving numeric 2019 0.07 1 1 1 1 0 ▁▁▇▁▁

participate_donation_discuss

Interested in: A one-time discussion about where other EAs are donating

Distribution

Distribution of values for participate_donation_discuss

Distribution of values for participate_donation_discuss

1854 missing values.

Summary statistics

name label data_type n_missing complete_rate min median max mean sd hist
participate_donation_discuss Interested in: A one-time discussion about where other EAs are donating numeric 1854 0.14 1 1 1 1 0 ▁▁▇▁▁

participate_social_event

Interested in: A one-time (virtual) social event to meet local EAs

Distribution

Distribution of values for participate_social_event

Distribution of values for participate_social_event

1721 missing values.

Summary statistics

name label data_type n_missing complete_rate min median max mean sd hist
participate_social_event Interested in: A one-time (virtual) social event to meet local EAs numeric 1721 0.2 1 1 1 1 0 ▁▁▇▁▁

participate_contact

May we (CEA) contact you if the activit(ies) you selected become(s) available?

Distribution

Distribution of values for participate_contact

Distribution of values for participate_contact

765 missing values.

Summary statistics

name label data_type n_missing complete_rate min median max mean sd hist
participate_contact May we (CEA) contact you if the activit(ies) you selected become(s) available? numeric 765 0.65 1 1 1 1 0 ▁▁▇▁▁

email_next_survey

Please send me an e-mail to next year’s survey

Distribution

Distribution of values for email_next_survey

Distribution of values for email_next_survey

0 missing values.

Summary statistics

name label data_type n_missing complete_rate n_unique empty min max whitespace
email_next_survey Please send me an e-mail to next year’s survey character 0 1 2 868 0 46 0

email_followup_surveys

Please e-mail me relevant followup surveys

Distribution

Distribution of values for email_followup_surveys

Distribution of values for email_followup_surveys

0 missing values.

Summary statistics

name label data_type n_missing complete_rate n_unique empty min max whitespace
email_followup_surveys Please e-mail me relevant followup surveys character 0 1 2 1289 0 42 0

email_dont_email

Don’t e-mail me about future surveys

Distribution

Distribution of values for email_dont_email

Distribution of values for email_dont_email

0 missing values.

Summary statistics

name label data_type n_missing complete_rate n_unique empty min max whitespace
email_dont_email Don’t e-mail me about future surveys character 0 1 2 2054 0 36 0

share_80k

Yes - I give my permission for this information to be shared with 80,000 Hours

Distribution

Distribution of values for share_80k

Distribution of values for share_80k

0 missing values.

Summary statistics

name label data_type n_missing complete_rate n_unique empty min max whitespace
share_80k Yes - I give my permission for this information to be shared with 80,000 Hours character 0 1 2 928 0 78 0

dont_share_80k

No - I do not wish for any of my information to be shared with 80,000 Hours

Distribution

Distribution of values for dont_share_80k

Distribution of values for dont_share_80k

1893 missing values.

Summary statistics

name label data_type n_missing complete_rate n_unique empty min max whitespace
dont_share_80k No - I do not wish for any of my information to be shared with 80,000 Hours character 1893 0.13 1 0 149 149 0

profile_ea_hub

Would you like a personal profile on the EA Hub?

Distribution

Distribution of values for profile_ea_hub

Distribution of values for profile_ea_hub

0 missing values.

Summary statistics

name label data_type n_missing complete_rate n_unique empty min max whitespace
profile_ea_hub Would you like a personal profile on the EA Hub? character 0 1 3 644 0 91 0

agree_quantify_compare_impact

Agree: It’s possible to roughly quantify and compare different types of impact

Distribution

Distribution of values for agree_quantify_compare_impact

Distribution of values for agree_quantify_compare_impact

1119 missing values.

Summary statistics

name label data_type ordered value_labels n_missing complete_rate n_unique top_counts
agree_quantify_compare_impact Agree: It’s possible to roughly quantify and compare different types of impact factor FALSE
    1. Strongly disagree,
      2. (2) Disagree,
      3. (3) Slightly disagree,
      4. (4) Neither agree nor disagree,
      5. (5) Slightly agree,
      6. (6) Agree,
      7. (7) Strongly agree
1119 0.48 6 (6): 505, (7): 354, (5): 150, (4): 16

agree_ways_better_than_others

Agree: Some ways of doing good are substantially better than others

Distribution

Distribution of values for agree_ways_better_than_others

Distribution of values for agree_ways_better_than_others

1117 missing values.

Summary statistics

name label data_type ordered value_labels n_missing complete_rate n_unique top_counts
agree_ways_better_than_others Agree: Some ways of doing good are substantially better than others factor FALSE
    1. Strongly disagree,
      2. (2) Disagree,
      3. (3) Slightly disagree,
      4. (4) Neither agree nor disagree,
      5. (5) Slightly agree,
      6. (6) Agree,
      7. (7) Strongly agree
1117 0.48 5 (7): 803, (6): 204, (5): 28, (4): 9

agree_work_on_any_cause

Agree: It makes sense to be open to working on any cause

Distribution

Distribution of values for agree_work_on_any_cause

Distribution of values for agree_work_on_any_cause

1122 missing values.

Summary statistics

name label data_type ordered value_labels n_missing complete_rate n_unique top_counts
agree_work_on_any_cause Agree: It makes sense to be open to working on any cause factor FALSE
    1. Strongly disagree,
      2. (2) Disagree,
      3. (3) Slightly disagree,
      4. (4) Neither agree nor disagree,
      5. (5) Slightly agree,
      6. (6) Agree,
      7. (7) Strongly agree
1122 0.48 7 (6): 371, (7): 370, (5): 156, (3): 57

agree_farmed_animals_concern

Agree: Farmed animals deserve our moral concern

Distribution

Distribution of values for agree_farmed_animals_concern

Distribution of values for agree_farmed_animals_concern

1114 missing values.

Summary statistics

name label data_type ordered value_labels n_missing complete_rate n_unique top_counts
agree_farmed_animals_concern Agree: Farmed animals deserve our moral concern factor FALSE
    1. Strongly disagree,
      2. (2) Disagree,
      3. (3) Slightly disagree,
      4. (4) Neither agree nor disagree,
      5. (5) Slightly agree,
      6. (6) Agree,
      7. (7) Strongly agree
1114 0.49 7 (7): 603, (6): 263, (5): 117, (4): 30

agree_longtermism

Agree: The impact of our actions on the very long-term future is most important

Distribution

Distribution of values for agree_longtermism

Distribution of values for agree_longtermism

1117 missing values.

Summary statistics

name label data_type ordered value_labels n_missing complete_rate n_unique top_counts
agree_longtermism Agree: The impact of our actions on the very long-term future is most important factor FALSE
    1. Strongly disagree,
      2. (2) Disagree,
      3. (3) Slightly disagree,
      4. (4) Neither agree nor disagree,
      5. (5) Slightly agree,
      6. (6) Agree,
      7. (7) Strongly agree
1117 0.48 7 (6): 263, (5): 242, (7): 213, (4): 143

reputation_effect_explanation

If possible, could you please explain your answer?

Distribution

Distribution of values for reputation_effect_explanation

Distribution of values for reputation_effect_explanation

1668 missing values.

Summary statistics

name label data_type n_missing complete_rate n_unique empty min max whitespace
reputation_effect_explanation If possible, could you please explain your answer? character 1668 0.23 496 0 3 1336 0

bottleneck_productivity

Are there any things which you think currently bottleneck your positive impact?

Distribution

Distribution of values for bottleneck_productivity

Distribution of values for bottleneck_productivity

1627 missing values.

Summary statistics

name label data_type n_missing complete_rate n_unique empty min max whitespace
bottleneck_productivity Are there any things which you think currently bottleneck your positive impact? character 1627 0.25 530 0 2 1200 0

dislike_ea_community

What do you personally dislike about the EA community and EA/EA-adjacent ideas?

Distribution

Distribution of values for dislike_ea_community

Distribution of values for dislike_ea_community

1611 missing values.

Summary statistics

name label data_type n_missing complete_rate n_unique empty min max whitespace
dislike_ea_community What do you personally dislike about the EA community and EA/EA-adjacent ideas? character 1611 0.26 545 0 1 2668 0

datecreated

Date Created

Distribution

Distribution of values for datecreated

Distribution of values for datecreated

0 missing values.

Summary statistics

name label data_type n_missing complete_rate n_unique empty min max whitespace
datecreated Date Created character 0 1 22 0 22 22 0

group_name_original

Distribution

Distribution of values for group_name_original

Distribution of values for group_name_original

1294 missing values.

Summary statistics

name label data_type n_missing complete_rate n_unique empty min max whitespace
group_name_original character 1294 0.4 442 0 5 324 0

group_name_manual

Group Name, manually assigned

Distribution

Distribution of values for group_name_manual

Distribution of values for group_name_manual

0 missing values.

Summary statistics

name label data_type n_missing complete_rate n_unique empty min max whitespace
group_name_manual Group Name, manually assigned character 0 1 213 1296 0 66 0

first_hear_qual

Distribution

Distribution of values for first_hear_qual

Distribution of values for first_hear_qual

0 missing values.

Summary statistics

name label data_type n_missing complete_rate n_unique empty min max whitespace
first_hear_qual character 0 1 127 1004 0 21 0

_merge {#_merge .tabset}

Distribution {#_merge_distribution}

Distribution of values for _merge

Distribution of values for _merge

0 missing values.

Summary statistics {#_merge_summary}

name label data_type ordered value_labels n_missing complete_rate n_unique top_counts
_merge factor FALSE
  1. master only (1),
    2. using only (2),
    3. matched (3),
    4. missing updated (4),
    5. nonmissing conflict (5)
0 1 1 mat: 2164, mas: 0, usi: 0, mis: 0

ea_id

Distribution

Distribution of values for ea_id

Distribution of values for ea_id

1937 missing values.

Summary statistics

name data_type n_missing complete_rate n_unique empty min max whitespace label
ea_id character 1937 0.1 227 0 32 32 0 NA

ea_id2

Distribution

Distribution of values for ea_id2

Distribution of values for ea_id2

175 missing values.

Summary statistics

name data_type n_missing complete_rate n_unique empty min max whitespace label
ea_id2 character 175 0.92 1932 0 32 32 0 NA

ea_id3

Distribution

Distribution of values for ea_id3

Distribution of values for ea_id3

1954 missing values.

Summary statistics

name data_type n_missing complete_rate n_unique empty min max whitespace label
ea_id3 character 1954 0.1 210 0 32 32 0 NA

engagement

Distribution

Distribution of values for engagement

Distribution of values for engagement

259 missing values.

Summary statistics

name data_type ordered value_labels n_missing complete_rate n_unique top_counts label
engagement factor FALSE
    1. No engagement,
      2. (2) Mild engagement,
      3. (3) Moderate engagement,
      4. (4) Considerable engagement,
      5. (5) High engagement
259 0.88 5 (3): 569, (4): 561, (5): 371, (2): 359 NA

capital_over_impact

Distribution

Distribution of values for capital_over_impact

Distribution of values for capital_over_impact

496 missing values.

Summary statistics

name data_type ordered value_labels n_missing complete_rate n_unique top_counts label
capital_over_impact factor FALSE
  1. Modestly prioritizing career capital,
    2. Modestly prioritizing immediate impact,
    3. N/A,
    4. Prioritizing both equally,
    5. Strongly prioritizing career capital,
    6. Strongly prioritizing immediate impact
496 0.77 6 Str: 438, Mod: 424, Pri: 279, Mod: 243 NA

financial_instability

Distribution

Distribution of values for financial_instability

Distribution of values for financial_instability

493 missing values.

Summary statistics

name data_type ordered value_labels n_missing complete_rate n_unique top_counts label
financial_instability factor FALSE
  1. Always,
    2. Never,
    3. Often,
    4. Prefer not to answer,
    5. Rarely,
    6. Sometimes
493 0.77 6 Nev: 753, Rar: 393, Som: 300, Oft: 136 NA

first_generation_student

Distribution

Distribution of values for first_generation_student

Distribution of values for first_generation_student

492 missing values.

Summary statistics

name data_type ordered value_labels n_missing complete_rate n_unique top_counts label
first_generation_student factor FALSE
  1. No,
    2. Yes
492 0.77 2 No: 1384, Yes: 288 NA

reputation_effect

Distribution

Distribution of values for reputation_effect

Distribution of values for reputation_effect

1169 missing values.

Summary statistics

name data_type ordered value_labels n_missing complete_rate n_unique top_counts label
reputation_effect factor FALSE
  1. No, no reputational consequences at all,
    2. Yes, a mix of reputational benefits and negative reputational costs,
    3. Yes, mostly negative reputational costs,
    4. Yes, mostly positive reputational benefits
1169 0.46 4 No,: 442, Yes: 307, Yes: 200, Yes: 46 NA

year_involved

Distribution

Distribution of values for year_involved

Distribution of values for year_involved

270 missing values.

Summary statistics

name data_type ordered value_labels n_missing complete_rate n_unique top_counts label
year_involved factor FALSE
  1. 2009 or before,
    2. 2010,
    3. 2011,
    4. 2012,
    5. 2013,
    6. 2014,
    7. 2015,
    8. 2016,
    9. 2017,
    10. 2018,
    11. 2019,
    12. 2020,
    13. I don’t remember
270 0.88 13 202: 329, 201: 292, 201: 261, 201: 254 NA

first_hear_ea

Distribution

Distribution of values for first_hear_ea

Distribution of values for first_hear_ea

254 missing values.

Summary statistics

name data_type ordered value_labels n_missing complete_rate n_unique top_counts label
first_hear_ea factor FALSE
  1. I don’t remember,
    2. 80,000 Hours,
    3. Animal Charity Evaluators,
    4. Book, article, or blog post,
    5. EA Global / EAGx,
    6. Educational course (e.g. lecture, class, MOOC),
    7. Facebook,
    8. GiveWell,
    9. Giving What We Can,
    10. LessWrong,
    11. Local or university EA group,
    12. One For The World,
    13. Other,
    14. Personal contact (e.g. friend, colleague, relative),
    15. Podcast,
    16. REG / EAF / FRI / The Swiss group,
    17. Search engine,
    18. Slate Star Codex,
    19. TED talk,
    20. The Life You Can Save (organization),
    21. Vox’s Future Perfect
254 0.88 21 Per: 310, 80,: 244, Boo: 179, Oth: 167 NA

city

Distribution

Distribution of values for city

Distribution of values for city

562 missing values.

Summary statistics

name data_type ordered value_labels n_missing complete_rate n_unique top_counts label
city factor FALSE
  1. Amsterdam,
    2. Auckland,
    3. Berlin,
    4. Boston / Cambridge (USA),
    5. Cambridge (UK),
    6. Canberra,
    7. Chicago,
    8. London,
    9. Los Angeles,
    10. Melbourne,
    11. New York City,
    12. Oslo,
    13. Other (please specify),
    14. Oxford,
    15. Philadelphia,
    16. SF Bay Area,
    17. Seattle,
    18. Stockholm,
    19. Sydney,
    20. Toronto,
    21. Vienna,
    22. Washington, DC,
    23. Zürich
562 0.74 23 Oth: 868, SF : 100, Lon: 90, New: 77 NA

collector_source

Distribution

Distribution of values for collector_source

Distribution of values for collector_source

0 missing values.

Summary statistics

name data_type ordered value_labels n_missing complete_rate n_unique top_counts label
collector_source factor FALSE
  1. 80K 2,
    2. 80K1,
    3. CE,
    4. CEA FB,
    5. EA FB,
    6. EA Forum,
    7. EA Forum backup,
    8. EA Newsletter,
    9. EAA newsletter?,
    10. EAS80K3,
    11. Email Invitation 1,
    12. GWWC,
    13. Groups FB,
    14. Groups newsletter?,
    15. Groups personal email?,
    16. Groups slack,
    17. Hangouts,
    18. LG Newsletter,
    19. LW,
    20. Reddit,
    21. SSC,
    22. Sharing,
    23. dankeamemes
0 1 23 EA : 426, 80K: 409, Ema: 227, EA : 220 NA

gender_manual

Distribution

Distribution of values for gender_manual

Distribution of values for gender_manual

536 missing values.

Summary statistics

name data_type ordered value_labels n_missing complete_rate n_unique top_counts label
gender_manual factor FALSE
  1. Other,
    2. Female,
    3. Male
536 0.75 3 Mal: 1148, Fem: 438, Oth: 42 NA

race_white

What is your race/ethnicity? White

Distribution

Distribution of values for race_white

Distribution of values for race_white

507 missing values.

Summary statistics

name label data_type n_missing complete_rate min median max mean sd hist
race_white What is your race/ethnicity? White numeric 507 0.77 0 1 1 0.83 0.38 ▂▁▁▁▇

race_black_aa

What is your race/ethnicity? Black or African American

Distribution

Distribution of values for race_black_aa

Distribution of values for race_black_aa

507 missing values.

Summary statistics

name label data_type n_missing complete_rate min median max mean sd hist
race_black_aa What is your race/ethnicity? Black or African American numeric 507 0.77 0 0 1 0.01 0.12 ▇▁▁▁▁

race_hispanic_la_spanish

What is your race/ethnicity? Hispanic, Latino or Spanish Origin

Distribution

Distribution of values for race_hispanic_la_spanish

Distribution of values for race_hispanic_la_spanish

507 missing values.

Summary statistics

name label data_type n_missing complete_rate min median max mean sd hist
race_hispanic_la_spanish What is your race/ethnicity? Hispanic, Latino or Spanish Origin numeric 507 0.77 0 0 1 0.04 0.2 ▇▁▁▁▁

race_american_indian_alaskan

What is your race/ethnicity? American Indian or Alaskan Native

Distribution

Distribution of values for race_american_indian_alaskan

Distribution of values for race_american_indian_alaskan

507 missing values.

Summary statistics

name label data_type n_missing complete_rate min median max mean sd hist
race_american_indian_alaskan What is your race/ethnicity? American Indian or Alaskan Native numeric 507 0.77 0 0 1 0 0.04 ▇▁▁▁▁

race_asian

What is your race/ethnicity? Asian

Distribution

Distribution of values for race_asian

Distribution of values for race_asian

507 missing values.

Summary statistics

name label data_type n_missing complete_rate min median max mean sd hist
race_asian What is your race/ethnicity? Asian numeric 507 0.77 0 0 1 0.12 0.33 ▇▁▁▁▁

race_native_hawaiin_pacific

What is your race/ethnicity? Native Hawaiian or Other Pacific Islander

Distribution

Distribution of values for race_native_hawaiin_pacific

Distribution of values for race_native_hawaiin_pacific

507 missing values.

Summary statistics

name label data_type n_missing complete_rate min median max mean sd hist
race_native_hawaiin_pacific What is your race/ethnicity? Native Hawaiian or Other Pacific Islander numeric 507 0.77 0 0 1 0 0.05 ▇▁▁▁▁

race_prefer_no_answer

What is your race/ethnicity? Prefer not to answer

Distribution

Distribution of values for race_prefer_no_answer

Distribution of values for race_prefer_no_answer

507 missing values.

Summary statistics

name label data_type n_missing complete_rate min median max mean sd hist
race_prefer_no_answer What is your race/ethnicity? Prefer not to answer numeric 507 0.77 0 0 1 0.03 0.16 ▇▁▁▁▁

race_other

What is your race/ethnicity? Other (please specify)

Distribution

Distribution of values for race_other

Distribution of values for race_other

507 missing values.

Summary statistics

name label data_type n_missing complete_rate min median max mean sd hist
race_other What is your race/ethnicity? Other (please specify) numeric 507 0.77 0 0 1 0.04 0.2 ▇▁▁▁▁

race_

Distribution

Distribution of values for race_

Distribution of values for race_

507 missing values.

Summary statistics

name data_type ordered value_labels n_missing complete_rate n_unique top_counts label
race_ factor FALSE
  1. american_indian_alaskan,
    2. asian,
    3. black_aa,
    4. hispanic_la_spanish,
    5. native_hawaiin_pacific,
    6. other,
    7. prefer_no_answer,
    8. white
507 0.77 8 whi: 1260, asi: 203, oth: 68, his: 59 NA

status_employed_ft

Employment/student status? Employed, full-time

Distribution

Distribution of values for status_employed_ft

Distribution of values for status_employed_ft

472 missing values.

Summary statistics

name label data_type n_missing complete_rate min median max mean sd hist
status_employed_ft Employment/student status? Employed, full-time numeric 472 0.78 0 0 1 0.49 0.5 ▇▁▁▁▇

status_employed_pt

Employment/student status? Employed, part time

Distribution

Distribution of values for status_employed_pt

Distribution of values for status_employed_pt

472 missing values.

Summary statistics

name label data_type n_missing complete_rate min median max mean sd hist
status_employed_pt Employment/student status? Employed, part time numeric 472 0.78 0 0 1 0.11 0.31 ▇▁▁▁▁

status_self_employed

Employment/student status? Self-employed

Distribution

Distribution of values for status_self_employed

Distribution of values for status_self_employed

472 missing values.

Summary statistics

name label data_type n_missing complete_rate min median max mean sd hist
status_self_employed Employment/student status? Self-employed numeric 472 0.78 0 0 1 0.11 0.31 ▇▁▁▁▁

status_not_employed_looking

Employment/student status? Not employed, but looking

Distribution

Distribution of values for status_not_employed_looking

Distribution of values for status_not_employed_looking

472 missing values.

Summary statistics

name label data_type n_missing complete_rate min median max mean sd hist
status_not_employed_looking Employment/student status? Not employed, but looking numeric 472 0.78 0 0 1 0.06 0.24 ▇▁▁▁▁

status_not_employed

Employment/student status? Not employed, but not looking

Distribution

Distribution of values for status_not_employed

Distribution of values for status_not_employed

472 missing values.

Summary statistics

name label data_type n_missing complete_rate min median max mean sd hist
status_not_employed Employment/student status? Not employed, but not looking numeric 472 0.78 0 0 1 0.02 0.16 ▇▁▁▁▁

status_homemaker_parent

Employment/student status? Homemaker / full-time parent

Distribution

Distribution of values for status_homemaker_parent

Distribution of values for status_homemaker_parent

472 missing values.

Summary statistics

name label data_type n_missing complete_rate min median max mean sd hist
status_homemaker_parent Employment/student status? Homemaker / full-time parent numeric 472 0.78 0 0 1 0.01 0.08 ▇▁▁▁▁

status_retired

Employment/student status? Retired

Distribution

Distribution of values for status_retired

Distribution of values for status_retired

472 missing values.

Summary statistics

name label data_type n_missing complete_rate min median max mean sd hist
status_retired Employment/student status? Retired numeric 472 0.78 0 0 1 0.02 0.15 ▇▁▁▁▁

status_student_hs

Employment/student status? Student (high school)

Distribution

Distribution of values for status_student_hs

Distribution of values for status_student_hs

472 missing values.

Summary statistics

name label data_type n_missing complete_rate min median max mean sd hist
status_student_hs Employment/student status? Student (high school) numeric 472 0.78 0 0 1 0.01 0.1 ▇▁▁▁▁

status_student_undergrad

Employment/student status? Student (undergraduate)

Distribution

Distribution of values for status_student_undergrad

Distribution of values for status_student_undergrad

472 missing values.

Summary statistics

name label data_type n_missing complete_rate min median max mean sd hist
status_student_undergrad Employment/student status? Student (undergraduate) numeric 472 0.78 0 0 1 0.18 0.38 ▇▁▁▁▂

status_student_masters

Employment/student status? Student (masters or equivalent)

Distribution

Distribution of values for status_student_masters

Distribution of values for status_student_masters

472 missing values.

Summary statistics

name label data_type n_missing complete_rate min median max mean sd hist
status_student_masters Employment/student status? Student (masters or equivalent) numeric 472 0.78 0 0 1 0.1 0.29 ▇▁▁▁▁

status_student_doctoral

Employment/student status? Student (doctoral degree or equivalent)

Distribution

Distribution of values for status_student_doctoral

Distribution of values for status_student_doctoral

472 missing values.

Summary statistics

name label data_type n_missing complete_rate min median max mean sd hist
status_student_doctoral Employment/student status? Student (doctoral degree or equivalent) numeric 472 0.78 0 0 1 0.07 0.26 ▇▁▁▁▁

status_student_other

Employment/student status? Student (other)

Distribution

Distribution of values for status_student_other

Distribution of values for status_student_other

472 missing values.

Summary statistics

name label data_type n_missing complete_rate min median max mean sd hist
status_student_other Employment/student status? Student (other) numeric 472 0.78 0 0 1 0.02 0.14 ▇▁▁▁▁

status_prefer_no_answer

Employment/student status? Prefer not to answer

Distribution

Distribution of values for status_prefer_no_answer

Distribution of values for status_prefer_no_answer

472 missing values.

Summary statistics

name label data_type n_missing complete_rate min median max mean sd hist
status_prefer_no_answer Employment/student status? Prefer not to answer numeric 472 0.78 0 0 1 0 0.06 ▇▁▁▁▁

status_

Distribution

Distribution of values for status_

Distribution of values for status_

472 missing values.

Summary statistics

name data_type ordered value_labels n_missing complete_rate n_unique top_counts label
status_ factor FALSE
  1. employed_ft,
    2. employed_pt,
    3. homemaker_parent,
    4. not_employed,
    5. not_employed_looking,
    6. prefer_no_answer,
    7. retired,
    8. self_employed,
    9. student_doctoral,
    10. student_hs,
    11. student_masters,
    12. student_other,
    13. student_undergrad
472 0.78 13 emp: 734, stu: 293, stu: 158, sel: 131 NA

career_still_deciding

Current career description? Still deciding what to pursue

Distribution

Distribution of values for career_still_deciding

Distribution of values for career_still_deciding

487 missing values.

Summary statistics

name label data_type n_missing complete_rate min median max mean sd hist
career_still_deciding Current career description? Still deciding what to pursue numeric 487 0.77 0 0 1 0.27 0.44 ▇▁▁▁▃

career_building_capital

Current career description? Building flexible career capital

Distribution

Distribution of values for career_building_capital

Distribution of values for career_building_capital

487 missing values.

Summary statistics

name label data_type n_missing complete_rate min median max mean sd hist
career_building_capital Current career description? Building flexible career capital numeric 487 0.77 0 0 1 0.29 0.45 ▇▁▁▁▃

career_non_profit_ea

Current career description? Work at a non-profit (EA organization)

Distribution

Distribution of values for career_non_profit_ea

Distribution of values for career_non_profit_ea

487 missing values.

Summary statistics

name label data_type n_missing complete_rate min median max mean sd hist
career_non_profit_ea Current career description? Work at a non-profit (EA organization) numeric 487 0.77 0 0 1 0.14 0.34 ▇▁▁▁▁

career_non_profit

Current career description? Work at a non-profit (not an EA organization)

Distribution

Distribution of values for career_non_profit

Distribution of values for career_non_profit

487 missing values.

Summary statistics

name label data_type n_missing complete_rate min median max mean sd hist
career_non_profit Current career description? Work at a non-profit (not an EA organization) numeric 487 0.77 0 0 1 0.06 0.24 ▇▁▁▁▁

career_for_profit_earn_to_give

Current career description? For profit (earning to give)

Distribution

Distribution of values for career_for_profit_earn_to_give

Distribution of values for career_for_profit_earn_to_give

487 missing values.

Summary statistics

name label data_type n_missing complete_rate min median max mean sd hist
career_for_profit_earn_to_give Current career description? For profit (earning to give) numeric 487 0.77 0 0 1 0.19 0.39 ▇▁▁▁▂

career_for_profit

Current career description? For profit (not earning to give)

Distribution

Distribution of values for career_for_profit

Distribution of values for career_for_profit

487 missing values.

Summary statistics

name label data_type n_missing complete_rate min median max mean sd hist
career_for_profit Current career description? For profit (not earning to give) numeric 487 0.77 0 0 1 0.13 0.34 ▇▁▁▁▁

career_academia

Current career description? Academia

Distribution

Distribution of values for career_academia

Distribution of values for career_academia

487 missing values.

Summary statistics

name label data_type n_missing complete_rate min median max mean sd hist
career_academia Current career description? Academia numeric 487 0.77 0 0 1 0.18 0.39 ▇▁▁▁▂

career_government

Current career description? Government

Distribution

Distribution of values for career_government

Distribution of values for career_government

487 missing values.

Summary statistics

name label data_type n_missing complete_rate min median max mean sd hist
career_government Current career description? Government numeric 487 0.77 0 0 1 0.09 0.28 ▇▁▁▁▁

career_think_tank_lobby

Current career description? Think tanks / lobbying / advocacy

Distribution

Distribution of values for career_think_tank_lobby

Distribution of values for career_think_tank_lobby

487 missing values.

Summary statistics

name label data_type n_missing complete_rate min median max mean sd hist
career_think_tank_lobby Current career description? Think tanks / lobbying / advocacy numeric 487 0.77 0 0 1 0.06 0.24 ▇▁▁▁▁

career_na

Current career description? N/A

Distribution

Distribution of values for career_na

Distribution of values for career_na

487 missing values.

Summary statistics

name label data_type n_missing complete_rate min median max mean sd hist
career_na Current career description? N/A numeric 487 0.77 0 0 1 0.03 0.18 ▇▁▁▁▁

career_other

Current career description? Other

Distribution

Distribution of values for career_other

Distribution of values for career_other

487 missing values.

Summary statistics

name label data_type n_missing complete_rate min median max mean sd hist
career_other Current career description? Other numeric 487 0.77 0 0 1 0.1 0.3 ▇▁▁▁▁

career_

Distribution

Distribution of values for career_

Distribution of values for career_

487 missing values.

Summary statistics

name data_type ordered value_labels n_missing complete_rate n_unique top_counts label
career_ factor FALSE
  1. academia,
    2. building_capital,
    3. for_profit,
    4. for_profit_earn_to_give,
    5. government,
    6. na,
    7. non_profit,
    8. non_profit_ea,
    9. other,
    10. still_deciding,
    11. think_tank_lobby
487 0.77 11 aca: 250, for: 246, bui: 209, for: 188 NA

race

Distribution

Distribution of values for race

Distribution of values for race

507 missing values.

Summary statistics

name data_type n_missing complete_rate n_unique empty min max whitespace label
race character 507 0.77 7 0 5 19 0 NA

age_approx

In which year were you born?

Distribution

Distribution of values for age_approx

Distribution of values for age_approx

505 missing values.

Summary statistics

name label data_type n_missing complete_rate min median max mean sd hist
age_approx In which year were you born? numeric 505 0.77 4 27 102 30 9.8 ▃▇▁▁▁

employ_status

Distribution

Distribution of values for employ_status

Distribution of values for employ_status

472 missing values.

Summary statistics

name data_type ordered value_labels n_missing complete_rate n_unique top_counts label
employ_status factor FALSE
  1. Employed (FT or self),
    2. Other (pt, unemployed, retired, homemaker, declined),
    3. Student
472 0.78 3 Emp: 865, Stu: 621, Oth: 206 NA

age_approx_ranges

Distribution

Distribution of values for age_approx_ranges

Distribution of values for age_approx_ranges

505 missing values.

Summary statistics

name data_type ordered value_labels n_missing complete_rate n_unique top_counts label
age_approx_ranges factor FALSE
  1. [4, 23),
    2. [23, 26),
    3. [26, 29),
    4. [29, 34),
    5. [34, 120)
505 0.77 5 [29: 396, [34: 345, [4,: 328, [23: 302 NA

age_approx_split

Distribution

Distribution of values for age_approx_split

Distribution of values for age_approx_split

505 missing values.

Summary statistics

name data_type ordered value_labels n_missing complete_rate n_unique top_counts label
age_approx_split factor FALSE
  1. [4, 27),
    2. [27, 120)
505 0.77 2 [27: 916, [4,: 743 NA

engagement_num

Distribution

Distribution of values for engagement_num

Distribution of values for engagement_num

259 missing values.

Summary statistics

name data_type n_missing complete_rate min median max mean sd hist label
engagement_num numeric 259 0.88 1 3 5 3.5 1.1 ▁▅▇▇▅ NA

engagement_f

Distribution

Distribution of values for engagement_f

Distribution of values for engagement_f

259 missing values.

Summary statistics

name data_type ordered value_labels n_missing complete_rate n_unique top_counts label
engagement_f factor FALSE
    1. No engagement,
      2. (2) Mild engagement,
      3. (3) Moderate engagement,
      4. (4) Considerable engagement,
      5. (5) High engagement
259 0.88 5 (3): 569, (4): 561, (5): 371, (2): 359 NA

d_engage_3_5

Distribution

Distribution of values for d_engage_3_5

Distribution of values for d_engage_3_5

259 missing values.

Summary statistics

name data_type n_missing complete_rate count mean label
d_engage_3_5 logical 259 0.88 TRU: 1501, FAL: 404 0.79 NA

d_engage_4_5

Distribution

Distribution of values for d_engage_4_5

Distribution of values for d_engage_4_5

259 missing values.

Summary statistics

name data_type n_missing complete_rate count mean label
d_engage_4_5 logical 259 0.88 FAL: 973, TRU: 932 0.49 NA

d_engage_5

Distribution

Distribution of values for d_engage_5

Distribution of values for d_engage_5

259 missing values.

Summary statistics

name data_type n_missing complete_rate count mean label
d_engage_5 logical 259 0.88 FAL: 1534, TRU: 371 0.19 NA

income_k

Distribution

Distribution of values for income_k

Distribution of values for income_k

665 missing values.

Summary statistics

name data_type n_missing complete_rate min median max mean sd hist label
income_k numeric 665 0.69 0 35 36000 152 1104 ▇▁▁▁▁ NA

d_male

Distribution

Distribution of values for d_male

Distribution of values for d_male

536 missing values.

Summary statistics

name data_type n_missing complete_rate min median max mean sd hist label
d_male numeric 536 0.75 0 1 1 0.71 0.46 ▃▁▁▁▇ NA

d_student

Distribution

Distribution of values for d_student

Distribution of values for d_student

472 missing values.

Summary statistics

name data_type n_missing complete_rate min median max mean sd hist label
d_student numeric 472 0.78 0 0 1 0.37 0.48 ▇▁▁▁▅ NA

d_live_usa

Distribution

Distribution of values for d_live_usa

Distribution of values for d_live_usa

0 missing values.

Summary statistics

name data_type n_missing complete_rate min median max mean sd hist label
d_live_usa numeric 0 1 0 0 1 0.3 0.46 ▇▁▁▁▃ NA

prioritize_lt

Distribution

Distribution of values for prioritize_lt

Distribution of values for prioritize_lt

908 missing values.

Summary statistics

name data_type n_missing complete_rate min median max mean sd hist label
prioritize_lt numeric 908 0.58 1 3.4 5 3.3 0.69 ▁▃▇▇▁ NA

referrer

Distribution

Distribution of values for referrer

Distribution of values for referrer

0 missing values.

Summary statistics

name data_type ordered value_labels n_missing complete_rate n_unique top_counts label
referrer factor FALSE
  1. 80K hours,
    2. CEA FB,
    3. dankeamemes,
    4. EA FB,
    5. EA Forum,
    6. EA Newsletter,
    7. Email; opt-in from prev. EAS,
    8. Giving What We Can,
    9. Groups FB,
    10. Groups personal email,
    11. Groups slack,
    12. Less Wrong,
    13. Reddit,
    14. Shared link,
    15. SlateStarCodex (Reddit group),
    16. Other
0 1 16 80K: 488, EA : 427, Ema: 227, EA : 220 NA

referrer_cat

Distribution

Distribution of values for referrer_cat

Distribution of values for referrer_cat

0 missing values.

Summary statistics

name data_type ordered value_labels n_missing complete_rate n_unique top_counts label
referrer_cat factor FALSE
  1. 80K hours,
    2. EA Forum,
    3. EA Newsletter,
    4. Email; opt-in from prev. EAS,
    5. Giving What We Can,
    6. Groups (local),
    7. Less Wrong or SlateStarCodex-Reddit,
    8. Reddit,
    9. Shared link,
    10. Social media (FB/memes),
    11. Other
0 1 11 80K: 488, EA : 427, Gro: 334, Ema: 227 NA

referrer_min100

Distribution

Distribution of values for referrer_min100

Distribution of values for referrer_min100

0 missing values.

Summary statistics

name data_type ordered value_labels n_missing complete_rate n_unique top_counts label
referrer_min100 factor FALSE
  1. 80K hours,
    2. EA Forum,
    3. EA Newsletter,
    4. Email; opt-in from prev. EAS,
    5. Groups personal email,
    6. Groups slack,
    7. Shared link,
    8. Other
0 1 8 80K: 488, EA : 427, Oth: 278, Ema: 227 NA

referrer_cat2

Distribution

Distribution of values for referrer_cat2

Distribution of values for referrer_cat2

0 missing values.

Summary statistics

name data_type n_missing complete_rate n_unique empty min max whitespace label
referrer_cat2 character 0 1 5 0 5 24 0 NA

referrer_cat3

Distribution

Distribution of values for referrer_cat3

Distribution of values for referrer_cat3

0 missing values.

Summary statistics

name data_type n_missing complete_rate n_unique empty min max whitespace label
referrer_cat3 character 0 1 5 0 5 30 0 NA

engage_cats_1

Distribution

Distribution of values for engage_cats_1

Distribution of values for engage_cats_1

259 missing values.

Summary statistics

name data_type n_missing complete_rate n_unique empty min max whitespace label
engage_cats_1 character 259 0.88 4 0 1 3 0 NA

engage_cats_2

Distribution

Distribution of values for engage_cats_2

Distribution of values for engage_cats_2

259 missing values.

Summary statistics

name data_type n_missing complete_rate n_unique empty min max whitespace label
engage_cats_2 character 259 0.88 3 0 1 3 0 NA

start_date_quantiles

Distribution

Distribution of values for start_date_quantiles

Distribution of values for start_date_quantiles

0 missing values.

Summary statistics

name data_type ordered value_labels n_missing complete_rate n_unique top_counts label
start_date_quantiles factor FALSE
  1. [0%, 20%),
    2. [20%, 40%],
    3. (40%, 60%],
    4. (60%, 80%],
    5. (80%, 100%]
0 1 5 (60: 540, [20: 461, (40: 429, [0%: 416 NA

start_date_thirds_by_referrer

Distribution

Distribution of values for start_date_thirds_by_referrer

Distribution of values for start_date_thirds_by_referrer

0 missing values.

Summary statistics

name data_type ordered value_labels n_missing complete_rate n_unique top_counts label
start_date_thirds_by_referrer factor FALSE
  1. [0%, 33.33%),
    2. [33.33%, 66.67%],
    3. (66.67%, 100%]
0 1 3 [33: 1004, (66: 641, [0%: 519 NA

survey_willing

Distribution

Distribution of values for survey_willing

Distribution of values for survey_willing

0 missing values.

Summary statistics

name data_type n_missing complete_rate n_unique empty min max whitespace label
survey_willing character 0 1 3 0 11 29 0 NA

donation_2019_c

Distribution

Distribution of values for donation_2019_c

Distribution of values for donation_2019_c

697 missing values.

Summary statistics

name data_type n_missing complete_rate min median max mean sd hist label
donation_2019_c numeric 697 0.68 0 528 2500000 7401 71727 ▇▁▁▁▁ NA

donation_2020_c

Distribution

Distribution of values for donation_2020_c

Distribution of values for donation_2020_c

718 missing values.

Summary statistics

name data_type n_missing complete_rate min median max mean sd hist label
donation_2020_c numeric 718 0.67 0 1003 2e+06 9836 73044 ▇▁▁▁▁ NA

income_c

Distribution

Distribution of values for income_c

Distribution of values for income_c

713 missing values.

Summary statistics

name data_type n_missing complete_rate min median max mean sd hist label
income_c numeric 713 0.67 0 33000 3e+06 60469 135751 ▇▁▁▁▁ NA

income_k_c

Distribution

Distribution of values for income_k_c

Distribution of values for income_k_c

713 missing values.

Summary statistics

name data_type n_missing complete_rate min median max mean sd hist label
income_k_c numeric 713 0.67 0 33 3000 60 136 ▇▁▁▁▁ NA

income_c_imp

Distribution

Distribution of values for income_c_imp

Distribution of values for income_c_imp

40 missing values.

Summary statistics

name data_type n_missing complete_rate min median max mean sd hist label
income_c_imp numeric 40 0.98 1.9 39600 3e+06 55887 112726 ▇▁▁▁▁ NA

don_share_inc_19

Distribution

Distribution of values for don_share_inc_19

Distribution of values for don_share_inc_19

794 missing values.

Summary statistics

name data_type n_missing complete_rate min median max mean hist label
don_share_inc_19 numeric 794 0.63 0 0.03 Inf Inf ▇▁▁▁▁ NA

don_share_inc_19_imp

Distribution

Distribution of values for don_share_inc_19_imp

Distribution of values for don_share_inc_19_imp

708 missing values.

Summary statistics

name data_type n_missing complete_rate min median max mean sd hist label
don_share_inc_19_imp numeric 708 0.67 0 0.022 67 0.13 1.8 ▇▁▁▁▁ NA

don_19_p1

Distribution

Distribution of values for don_19_p1

Distribution of values for don_19_p1

697 missing values.

Summary statistics

name data_type n_missing complete_rate min median max mean sd hist label
don_19_p1 numeric 697 0.68 1 529 2500001 7402 71727 ▇▁▁▁▁ NA

income_c_imp_k

Distribution

Distribution of values for income_c_imp_k

Distribution of values for income_c_imp_k

40 missing values.

Summary statistics

name data_type n_missing complete_rate min median max mean sd hist label
income_c_imp_k numeric 40 0.98 0.0019 40 3000 56 113 ▇▁▁▁▁ NA

action_gwwc_f

Distribution

Distribution of values for action_gwwc_f

Distribution of values for action_gwwc_f

0 missing values.

Summary statistics

name data_type ordered value_labels n_missing complete_rate n_unique top_counts label
action_gwwc_f factor FALSE
  1. 0,
    2. 1
0 1 2 0: 1594, 1: 570 NA

top_priority_rating

Distribution

Distribution of values for top_priority_rating

Distribution of values for top_priority_rating

0 missing values.

Summary statistics

name data_type n_missing complete_rate min median max mean hist label
top_priority_rating numeric 0 1 -Inf 5 5 -Inf ▁▁▁▃▇ NA

avg_priority_rating

Distribution

Distribution of values for avg_priority_rating

Distribution of values for avg_priority_rating

491 missing values.

Summary statistics

name data_type n_missing complete_rate min median max mean sd hist label
avg_priority_rating numeric 491 0.77 1.7 3.2 5 3.3 0.49 ▁▅▇▂▁ NA

mn_priority_rating

Distribution

Distribution of values for mn_priority_rating

Distribution of values for mn_priority_rating

491 missing values.

Summary statistics

name data_type n_missing complete_rate min median max mean sd hist label
mn_priority_rating numeric 491 0.77 1.7 3.2 5 3.3 0.49 ▁▅▇▂▁ NA

lt_top_priority

Distribution

Distribution of values for lt_top_priority

Distribution of values for lt_top_priority

491 missing values.

Summary statistics

name data_type n_missing complete_rate count mean label
lt_top_priority logical 491 0.77 TRU: 852, FAL: 821 0.51 NA

lt_above_mn_priority

Distribution

Distribution of values for lt_above_mn_priority

Distribution of values for lt_above_mn_priority

524 missing values.

Summary statistics

name data_type n_missing complete_rate count mean label
lt_above_mn_priority logical 524 0.76 TRU: 825, FAL: 815 0.5 NA

top_priority_rating_among_lt

Distribution

Distribution of values for top_priority_rating_among_lt

Distribution of values for top_priority_rating_among_lt

0 missing values.

Summary statistics

name data_type n_missing complete_rate min median max mean hist label
top_priority_rating_among_lt numeric 0 1 -Inf 4 5 -Inf ▁▁▃▇▆ NA

mn_priority_lt_rating

Distribution

Distribution of values for mn_priority_lt_rating

Distribution of values for mn_priority_lt_rating

524 missing values.

Summary statistics

name data_type n_missing complete_rate min median max mean sd hist label
mn_priority_lt_rating numeric 524 0.76 1 3.4 5 3.3 0.71 ▁▃▇▇▂ NA

start_date_qtl_by_referrer

Distribution

Distribution of values for start_date_qtl_by_referrer

Distribution of values for start_date_qtl_by_referrer

0 missing values.

Summary statistics

name data_type ordered value_labels n_missing complete_rate n_unique top_counts label
start_date_qtl_by_referrer factor FALSE
  1. [0%, 25%),
    2. [25%, 50%],
    3. (50%, 75%],
    4. (75%, 100%]
0 1 4 [25: 802, (50: 588, (75: 426, [0%: 348 NA

Missingness report

descriptionincome_c_impincome_c_imp_kea_id2first_hear_eaengagementengagement_numengagement_fd_engage_3_5d_engage_4_5d_engage_5engage_cats_1engage_cats_2year_involvedaction_chose_job_degreeaction_applied_job_degreeaction_donatedaction_gwwcaction_organize_groupaction_work_ea_orgaction_change_majoraction_wrote_thesisaction_internshipaction_applied_ea_globalaction_attended_ea_globalaction_ea_forumaction_lead_groupaction_applied_one_on_oneaction_had_one_on_oneaction_change_careeraction_subscribe_80kaction_noneinvolve_80kinvolve_givewellinvolve_personal_contactinvolve_bookinvolve_article_bloginvolve_gwwcinvolve_groupinvolve_onlineinvolve_lesswronginvolve_slate_starinvolve_podcastinvolve_ea_globalinvolve_lycsinvolve_aceinvolve_eagxinvolve_othermember_ea_fbmember_ea_forummember_lesswrongmember_ea_groupmember_noneinfluence_80k_one_on_oneinfluence_80k_websiteinfluence_80k_podcastinfluence_podcast_otherinfluence_personal_contactinfluence_booksinfluence_gwwcinfluence_local_groupinfluence_givewellinfluence_ea_globalinfluence_eagxinfluence_aceinfluence_lycsinfluence_ea_foruminfluence_articles_blogsinfluence_ea_surveyinfluence_facebook_groupsinfluence_lesswronginfluence_slate_starinfluence_wanbaminfluence_aacinfluence_noneinfluence_otherstatus_employed_ftstatus_employed_ptstatus_self_employedstatus_not_employed_lookingstatus_not_employedstatus_homemaker_parentstatus_retiredstatus_student_hsstatus_student_undergradstatus_student_mastersstatus_student_doctoralstatus_student_otherstatus_prefer_no_answerstatus_employ_statusd_studentcareer_still_decidingcareer_building_capitalcareer_non_profit_eacareer_non_profitcareer_for_profit_earn_to_givecareer_for_profitcareer_academiacareer_governmentcareer_think_tank_lobbycareer_nacareer_othercareer_lt_top_priorityfirst_generation_studentfinancial_instabilitycapital_over_impactbirth_yearage_approxage_approx_rangesage_approx_splitrace_whiterace_black_aarace_hispanic_la_spanishrace_american_indian_alaskanrace_asianrace_native_hawaiin_pacificrace_prefer_no_answerrace_otherrace_racelt_above_mn_prioritygender_originalgender_manuald_maleprioritize_global_povertycurrencyprioritize_animal_welfareprioritize_climate_changecityfriend_introduceprioritize_biosecurityagree_part_of_ea_communityprioritize_ai_risksagree_ea_helps_impactea_community_idealea_community_satisfactionprioritize_ea_movementprioritize_mental_healthdonation_2019prioritize_nuclear_securityincomeincome_kdonation_2020prioritize_x_riskssexual_orientationprioritize_causesdonation_2019_cdon_19_p1don_share_inc_19_impuniversity_originalincome_cincome_k_cdonation_2020_cdon_share_inc_19prioritize_broad_longtermismparticipate_contactlearned_80kconnection_80klearned_ea_globalconnection_ea_globallearned_ea_hubconnection_ea_hublearned_ea_student_mentoringconnection_ea_student_mentorlearned_eagxconnection_eagxlearned_effective_thesisconnection_effective_thesislearned_facebook_groupconnection_facebook_grouplearned_gwwcconnection_gwwclearned_intl_ea_eventsconnection_intl_ea_eventslearned_personal_connectionconnection_personal_contactlearned_lesswrongconnection_lesswronglearned_local_groupconnection_local_groupslearned_non_local_groupconnection_non_local_grouplearned_ea_forumconnection_ea_forumlearned_ea_booksconnection_ea_bookslearned_ea_newsletterconnection_ea_newsletterlearned_noneconnection_nonelearned_connection_otherprioritize_ltfirst_hear_ea_descnegative_80knegative_podcastnegative_givewellnegative_personal_contactnegative_booksnegative_gwwcnegative_local_groupnegative_lesswrongnegative_slate_starnegative_ea_globalnegative_eagxnegative_facebook_groupnegative_ea_forumnegative_articles_blogsnegative_ea_fellowshipnegative_eagx2negative_ea_newsletternegative_wanbamnegative_nonenegative_otherengaged_personal_contactea_community_whyprioritize_metaagree_farmed_animals_concernagree_ways_better_than_othersagree_longtermismagree_quantify_compare_impactagree_work_on_any_causereputation_effectengaged_80k_hoursgroup_comfortable_friendlocal_group_originalgroup_name_originalcity_othergroup_supports_actionengaged_80k_podcastgroup_beliefs_humilityengaged_local_groupsengaged_online_communityengaged_givewellengaged_ea_forumengaged_ea_newsletterengaged_slate_starengaged_lesswrongdislike_ea_communitybottleneck_productivityreputation_effect_explanationengaged_gwwcparticipate_fellowship_causesprioritize_othersubstantial_affect_impactparticipate_fellowship_advea_org_or_projectparticipate_social_eventparticipate_fellowship_careerengaged_eagxengaged_ea_globalnegative_responseparticipate_the_precipiceparticipate_donation_discussdont_share_80kparticipate_80k_pod_discussdonate_other1engaged_ea_fellowshipea_idparticipate_doing_good_betterea_id3participate_fellowship_introfirst_hear_ea_otherparticipate_gwwc_info_sessionparticipate_intro_one_on_oneengaged_80k_one_on_oneengaged_wanbamcustom_data_1var_missn_miss
Missing values per variable40       40       175       254      259      259      259      259      259      259      259      259      270       280       280       280       280       280       280       280       280       280       280       280       280       280       280       280       280       280       280       290       290       290       290       290       290       290       290       290       290       290       290       290       290       290       290       310       310       310       310       310       413       413       413       413       413       413       413       413       413       413       413       413       413       413       413       413       413       413       413       413       413       413       413       472       472       472       472       472       472       472       472       472       472       472       472       472       472       472       472       487       487       487       487       487       487       487       487       487       487       487       487       491       492       493       496       505       505       505       505       507       507       507       507       507       507       507       507       507       507       524       526       536       536       539       555       561      561      562      581       583       584       601       603       617       624       639       641       647       652       665      665      669      678       686       689       697       697       708       712       713       713       718       723       758       765      829       829       829       829       829       829       829       829       829       829       829       829       829       829       829       829       829       829       829       829       829       829       829       829       829       829       829       829       829       829       829       829       829       829       829       908       968       1.03e+031.03e+031.03e+031.03e+031.03e+031.03e+031.03e+031.03e+031.03e+031.03e+031.03e+031.03e+031.03e+031.03e+031.03e+031.03e+031.03e+031.03e+031.03e+031.03e+031.07e+031.1e+03 1.11e+031.11e+031.12e+031.12e+031.12e+031.12e+031.17e+031.23e+031.29e+031.29e+031.29e+031.3e+031.3e+031.3e+031.3e+031.32e+031.36e+031.41e+031.44e+031.53e+031.59e+031.6e+031.61e+031.63e+031.67e+031.67e+031.69e+031.7e+031.7e+031.7e+031.72e+031.72e+031.74e+031.78e+031.79e+031.81e+031.85e+031.85e+031.89e+031.9e+031.91e+031.94e+031.94e+031.94e+031.95e+031.97e+032e+032.02e+032.03e+032.04e+032.06e+032.16e+032.06e+052.06e+05
Missing values in 265 variables1       1       1       0      0      0      0      0      0      0      0      0      0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0      0      0      0       0       0       0       0       0       0       0       0       0       0       0      0      0      0       0       0       0       0       0       0       0       0       0       0       0       0      0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0      0      0      0      0       0       0       0       0       0       0      0       0       0       0       0       0      0      0      0       0       0       0       0       0       0       0       0       0      0       0       0       0       0       0       00       0       0       0       0       265       227       
Missing values in 216 variables1       1       1       1      1      1      1      1      1      1      1      1      1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0      0      0      0       0       0       0       0       0       0       0       0       0       0       0      0      0      0       0       0       0       0       0       0       0       0       0       0       0       0      0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0      0      0      0      0       0       0       0       0       0       0      0       0       0       0       0       0      0      0      0       0       0       0       0       0       0       0       0       0      0       0       0       0       0       0       00       0       0       0       0       216       34       
Missing values in 215 variables1       1       1       1      1      1      1      1      1      1      1      1      1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       1       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0      0      0      0       0       0       0       0       0       0       0       0       0       0       0      0      0      0       0       0       0       0       0       0       0       0       0       0       0       0      0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       1       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0       0      0      0      0      0       0       0       0       0       0       0      0       0       0       0       0       0      0      0      0       0       0       0       0       0       0       0       0       0      0       0       0       0       0       0       00       0       0       0       0       215       32       
1817 other, less frequent patterns1.78e+031.78e+031.66e+031.8e+031.8e+031.8e+031.8e+031.8e+031.8e+031.8e+031.8e+031.8e+031.79e+031.78e+031.78e+031.78e+031.78e+031.78e+031.78e+031.78e+031.78e+031.78e+031.78e+031.78e+031.78e+031.78e+031.78e+031.78e+031.78e+031.78e+031.78e+031.77e+031.77e+031.77e+031.77e+031.77e+031.77e+031.77e+031.77e+031.77e+031.77e+031.77e+031.77e+031.77e+031.77e+031.77e+031.77e+031.76e+031.76e+031.76e+031.76e+031.76e+031.75e+031.75e+031.75e+031.75e+031.75e+031.75e+031.75e+031.75e+031.75e+031.75e+031.75e+031.75e+031.75e+031.75e+031.75e+031.75e+031.75e+031.75e+031.75e+031.75e+031.75e+031.75e+031.75e+031.69e+031.69e+031.69e+031.69e+031.69e+031.69e+031.69e+031.69e+031.69e+031.69e+031.69e+031.69e+031.69e+031.69e+031.69e+031.69e+031.68e+031.68e+031.68e+031.68e+031.68e+031.68e+031.68e+031.68e+031.68e+031.68e+031.68e+031.68e+031.67e+031.67e+031.67e+031.67e+031.66e+031.66e+031.66e+031.66e+031.66e+031.66e+031.66e+031.66e+031.66e+031.66e+031.66e+031.66e+031.66e+031.66e+031.64e+031.64e+031.63e+031.63e+031.62e+031.61e+031.6e+031.6e+031.6e+031.58e+031.58e+031.58e+031.56e+031.56e+031.55e+031.54e+031.52e+031.52e+031.52e+031.51e+031.5e+031.5e+031.5e+031.49e+031.48e+031.48e+031.47e+031.47e+031.46e+031.45e+031.45e+031.45e+031.45e+031.44e+031.41e+031.4e+031.34e+031.34e+031.34e+031.34e+031.34e+031.34e+031.34e+031.34e+031.34e+031.34e+031.34e+031.34e+031.34e+031.34e+031.34e+031.34e+031.34e+031.34e+031.34e+031.34e+031.34e+031.34e+031.34e+031.34e+031.34e+031.34e+031.34e+031.34e+031.34e+031.34e+031.34e+031.34e+031.34e+031.34e+031.34e+031.26e+031.14e+031.14e+031.14e+031.14e+031.14e+031.14e+031.14e+031.14e+031.14e+031.14e+031.14e+031.14e+031.14e+031.14e+031.14e+031.14e+031.14e+031.14e+031.14e+031.14e+031.14e+031.1e+03 1.06e+031.06e+031.05e+031.05e+031.05e+031.04e+031.04e+03995       930       861       857       857       868      854      866      851      844       802       754       721       636       575       563      553       537       496       491       470       467      465      462      441       443       429       389       374       355       317       310       271       263      252       227       221       223       210       191       160145       134       119       109       0       1.2e+05 1.87e+03

Codebook table

JSON-LD metadata

The following JSON-LD can be found by search engines, if you share this codebook publicly on the web.

{
  "name": ".",
  "datePublished": "2021-03-03",
  "description": "The dataset has N=2164 rows and 310 columns.\n0 rows have no missing values on any column.\n\n\n## Table of variables\nThis table contains variable names, labels, and number of missing values.\nSee the complete codebook for more.\n\n[truncated]\n\n### Note\nThis dataset was automatically described using the [codebook R package](https://rubenarslan.github.io/codebook/) (version 0.9.2).",
  "keywords": ["respondentid", "collectorid", "start_date", "end_date", "custom_data_1", "opt_out_cea", "first_hear_ea_other", "first_hear_ea_desc", "involve_80k", "involve_givewell", "involve_personal_contact", "involve_book", "involve_article_blog", "involve_gwwc", "involve_group", "involve_online", "involve_lesswrong", "involve_slate_star", "involve_podcast", "involve_ea_global", "involve_lycs", "involve_ace", "involve_eagx", "involve_other", "action_chose_job_degree", "action_applied_job_degree", "action_donated", "action_gwwc", "action_organize_group", "action_work_ea_org", "action_change_major", "action_wrote_thesis", "action_internship", "action_applied_ea_global", "action_attended_ea_global", "action_ea_forum", "action_lead_group", "action_applied_one_on_one", "action_had_one_on_one", "action_change_career", "action_subscribe_80k", "action_none", "ea_org_or_project", "member_ea_fb", "member_ea_forum", "member_lesswrong", "member_ea_group", "member_none", "local_group_original", "group_comfortable_friend", "group_beliefs_humility", "group_supports_action", "influence_80k_one_on_one", "influence_80k_website", "influence_80k_podcast", "influence_podcast_other", "influence_personal_contact", "influence_books", "influence_gwwc", "influence_local_group", "influence_givewell", "influence_ea_global", "influence_eagx", "influence_ace", "influence_lycs", "influence_ea_forum", "influence_articles_blogs", "influence_ea_survey", "influence_facebook_groups", "influence_lesswrong", "influence_slate_star", "influence_wanbam", "influence_aac", "influence_none", "influence_other", "negative_80k", "negative_podcast", "negative_givewell", "negative_personal_contact", "negative_books", "negative_gwwc", "negative_local_group", "negative_lesswrong", "negative_slate_star", "negative_ea_global", "negative_eagx", "negative_facebook_group", "negative_ea_forum", "negative_articles_blogs", "negative_ea_fellowship", "negative_eagx2", "negative_ea_newsletter", "negative_wanbam", "negative_none", "negative_other", "negative_response", "engaged_ea_forum", "engaged_online_community", "engaged_local_groups", "engaged_ea_fellowship", "engaged_gwwc", "engaged_ea_global", "engaged_eagx", "engaged_ea_newsletter", "engaged_wanbam", "engaged_personal_contact", "engaged_80k_podcast", "engaged_80k_hours", "engaged_80k_one_on_one", "engaged_givewell", "engaged_lesswrong", "engaged_slate_star", "substantial_affect_impact", "prioritize_animal_welfare", "prioritize_causes", "prioritize_climate_change", "prioritize_biosecurity", "prioritize_nuclear_security", "prioritize_ai_risks", "prioritize_mental_health", "prioritize_global_poverty", "prioritize_meta", "prioritize_ea_movement", "prioritize_x_risks", "prioritize_broad_longtermism", "prioritize_other", "currency", "currency_other", "income", "donation_2019", "donation_2020", "donate_later", "university_original", "birth_year", "gender_original", "sexual_orientation", "country", "city_other", "ea_community_ideal", "ea_community_satisfaction", "ea_community_why", "agree_ea_helps_impact", "agree_part_of_ea_community", "friend_introduce", "learned_80k", "connection_80k", "learned_ea_global", "connection_ea_global", "learned_ea_hub", "connection_ea_hub", "learned_ea_student_mentoring", "connection_ea_student_mentor", "learned_eagx", "connection_eagx", "learned_effective_thesis", "connection_effective_thesis", "learned_facebook_group", "connection_facebook_group", "learned_gwwc", "connection_gwwc", "learned_intl_ea_events", "connection_intl_ea_events", "learned_personal_connection", "connection_personal_contact", "learned_lesswrong", "connection_lesswrong", "learned_local_group", "connection_local_groups", "learned_non_local_group", "connection_non_local_group", "learned_ea_forum", "connection_ea_forum", "learned_ea_books", "connection_ea_books", "learned_ea_newsletter", "connection_ea_newsletter", "learned_none", "connection_none", "learned_connection_other", "participate_doing_good_better", "participate_the_precipice", "participate_fellowship_intro", "participate_fellowship_adv", "participate_80k_pod_discuss", "participate_fellowship_career", "participate_fellowship_causes", "participate_intro_one_on_one", "participate_gwwc_info_session", "participate_donation_discuss", "participate_social_event", "participate_contact", "email_next_survey", "email_followup_surveys", "email_dont_email", "share_80k", "dont_share_80k", "profile_ea_hub", "agree_quantify_compare_impact", "agree_ways_better_than_others", "agree_work_on_any_cause", "agree_farmed_animals_concern", "agree_longtermism", "reputation_effect_explanation", "bottleneck_productivity", "dislike_ea_community", "donate_rethink_charity", "donate_80k", "donate_center_applied_rational", "donate_mercy_for_animals", "donate_other1", "donate_other2", "donate_other3", "donate_other4", "donate_other5", "datecreated", "group_name_original", "group_name_manual", "first_hear_qual", "_merge", "ea_id", "ea_id2", "ea_id3", "engagement", "capital_over_impact", "financial_instability", "first_generation_student", "reputation_effect", "year_involved", "first_hear_ea", "city", "collector_source", "gender_manual", "race_white", "race_black_aa", "race_hispanic_la_spanish", "race_american_indian_alaskan", "race_asian", "race_native_hawaiin_pacific", "race_prefer_no_answer", "race_other", "race_", "status_employed_ft", "status_employed_pt", "status_self_employed", "status_not_employed_looking", "status_not_employed", "status_homemaker_parent", "status_retired", "status_student_hs", "status_student_undergrad", "status_student_masters", "status_student_doctoral", "status_student_other", "status_prefer_no_answer", "status_", "career_still_deciding", "career_building_capital", "career_non_profit_ea", "career_non_profit", "career_for_profit_earn_to_give", "career_for_profit", "career_academia", "career_government", "career_think_tank_lobby", "career_na", "career_other", "career_", "race", "age_approx", "employ_status", "age_approx_ranges", "age_approx_split", "engagement_num", "engagement_f", "d_engage_3_5", "d_engage_4_5", "d_engage_5", "income_k", "d_male", "d_student", "d_live_usa", "prioritize_lt", "referrer", "referrer_cat", "referrer_min100", "referrer_cat2", "referrer_cat3", "engage_cats_1", "engage_cats_2", "start_date_quantiles", "start_date_thirds_by_referrer", "survey_willing", "donation_2019_c", "donation_2020_c", "income_c", "income_k_c", "income_c_imp", "don_share_inc_19", "don_share_inc_19_imp", "don_19_p1", "income_c_imp_k", "action_gwwc_f", "top_priority_rating", "avg_priority_rating", "mn_priority_rating", "lt_top_priority", "lt_above_mn_priority", "top_priority_rating_among_lt", "mn_priority_lt_rating", "start_date_qtl_by_referrer"],
  "@context": "http://schema.org/",
  "@type": "Dataset",
  "variableMeasured": [
    {
      "name": "respondentid",
      "description": "Respondent ID ",
      "@type": "propertyValue"
    },
    {
      "name": "collectorid",
      "description": "Collector ID ",
      "@type": "propertyValue"
    },
    {
      "name": "start_date",
      "description": "Start Date ",
      "@type": "propertyValue"
    },
    {
      "name": "end_date",
      "description": "End Date ",
      "@type": "propertyValue"
    },
    {
      "name": "custom_data_1",
      "description": "Custom Data 1 ",
      "@type": "propertyValue"
    },
    {
      "name": "opt_out_cea",
      "description": "Opt out of data sharing with the Centre for Effective Altruism ",
      "@type": "propertyValue"
    },
    {
      "name": "first_hear_ea_other",
      "description": "How did you first hear about effective altruism? Other",
      "@type": "propertyValue"
    },
    {
      "name": "first_hear_ea_desc",
      "description": "Please briefly specify any further details about how you first heard about EA. ",
      "@type": "propertyValue"
    },
    {
      "name": "involve_80k",
      "description": "Important for you getting involved in EA? 80,000 Hours",
      "@type": "propertyValue"
    },
    {
      "name": "involve_givewell",
      "description": "Important for you getting involved in EA? GiveWell",
      "@type": "propertyValue"
    },
    {
      "name": "involve_personal_contact",
      "description": "Important for you getting involved in EA? Personal contact with EAs",
      "@type": "propertyValue"
    },
    {
      "name": "involve_book",
      "description": "Important for you getting involved in EA? A book",
      "@type": "propertyValue"
    },
    {
      "name": "involve_article_blog",
      "description": "Important for you getting involved in EA? An article or blog",
      "@type": "propertyValue"
    },
    {
      "name": "involve_gwwc",
      "description": "Important for you getting involved in EA? Giving What We Can",
      "@type": "propertyValue"
    },
    {
      "name": "involve_group",
      "description": "Important for you getting involved in EA? Local or university EA Group",
      "@type": "propertyValue"
    },
    {
      "name": "involve_online",
      "description": "Important for you getting involved in EA? The online EA community",
      "@type": "propertyValue"
    },
    {
      "name": "involve_lesswrong",
      "description": "Important for you getting involved in EA? LessWrong",
      "@type": "propertyValue"
    },
    {
      "name": "involve_slate_star",
      "description": "Important for you getting involved in EA? Slate Star Codex",
      "@type": "propertyValue"
    },
    {
      "name": "involve_podcast",
      "description": "Important for you getting involved in EA? Podcast",
      "@type": "propertyValue"
    },
    {
      "name": "involve_ea_global",
      "description": "Important for you getting involved in EA? EA Global",
      "@type": "propertyValue"
    },
    {
      "name": "involve_lycs",
      "description": "Important for you getting involved in EA? The Life You Can Save",
      "@type": "propertyValue"
    },
    {
      "name": "involve_ace",
      "description": "Important for you getting involved in EA? Animal Charity Evaluators",
      "@type": "propertyValue"
    },
    {
      "name": "involve_eagx",
      "description": "Important for you getting involved in EA? EAGx",
      "@type": "propertyValue"
    },
    {
      "name": "involve_other",
      "description": "Important for you getting involved in EA? Other (please specify)",
      "@type": "propertyValue"
    },
    {
      "name": "action_chose_job_degree",
      "description": "Action: Chose a job or graduate degree program based on EA principles",
      "@type": "propertyValue"
    },
    {
      "name": "action_applied_job_degree",
      "description": "Action: Applied for a job or graduate degree program based on EA principles",
      "@type": "propertyValue"
    },
    {
      "name": "action_donated",
      "description": "Action: Donated >10% of your income based on EA principles",
      "@type": "propertyValue"
    },
    {
      "name": "action_gwwc",
      "description": "Action: Took the Giving What We Can pledge",
      "@type": "propertyValue"
    },
    {
      "name": "action_organize_group",
      "description": "Action: Spent >6 hours/week for >=2 months organizing an EA group/project",
      "@type": "propertyValue"
    },
    {
      "name": "action_work_ea_org",
      "description": "Action: Worked (or currently work) at an EA organization",
      "@type": "propertyValue"
    },
    {
      "name": "action_change_major",
      "description": "Action: Changed your major in university based on EA principles",
      "@type": "propertyValue"
    },
    {
      "name": "action_wrote_thesis",
      "description": "Action: Wrote a thesis based on EA principles",
      "@type": "propertyValue"
    },
    {
      "name": "action_internship",
      "description": "Action: Internship related to a career path you are exploring based on EA",
      "@type": "propertyValue"
    },
    {
      "name": "action_applied_ea_global",
      "description": "Action: Applied to EA Global",
      "@type": "propertyValue"
    },
    {
      "name": "action_attended_ea_global",
      "description": "Action: Attended EA Global",
      "@type": "propertyValue"
    },
    {
      "name": "action_ea_forum",
      "description": "Action: Posted or commented on the EA Forum",
      "@type": "propertyValue"
    },
    {
      "name": "action_lead_group",
      "description": "Action: Been a leader of a local EA group",
      "@type": "propertyValue"
    },
    {
      "name": "action_applied_one_on_one",
      "description": "Action: Applied for a one-on-one career discussion with 80,000 Hours",
      "@type": "propertyValue"
    },
    {
      "name": "action_had_one_on_one",
      "description": "Action: Had a one-on-one career discussion with 80,000 Hours",
      "@type": "propertyValue"
    },
    {
      "name": "action_change_career",
      "description": "Action: Changed your career plans based on EA principles",
      "@type": "propertyValue"
    },
    {
      "name": "action_subscribe_80k",
      "description": "Action: Subscribed to the 80,000 Hours newsletter",
      "@type": "propertyValue"
    },
    {
      "name": "action_none",
      "description": "Action: None of the above",
      "@type": "propertyValue"
    },
    {
      "name": "ea_org_or_project",
      "description": "Name of EA org/project you worked on or interned for. ",
      "@type": "propertyValue"
    },
    {
      "name": "member_ea_fb",
      "description": "Which of the following are you a member of? EA Facebook group",
      "@type": "propertyValue"
    },
    {
      "name": "member_ea_forum",
      "description": "Which of the following are you a member of? The Effective Altruism Forum",
      "@type": "propertyValue"
    },
    {
      "name": "member_lesswrong",
      "description": "Which of the following are you a member of? LessWrong",
      "@type": "propertyValue"
    },
    {
      "name": "member_ea_group",
      "description": "Which of the following are you a member of? Local EA group",
      "@type": "propertyValue"
    },
    {
      "name": "member_none",
      "description": "Which of the following are you a member of? None of the above",
      "@type": "propertyValue"
    },
    {
      "name": "local_group_original",
      "description": "If you are a member of a local EA group, which group are you a member of? ",
      "@type": "propertyValue"
    },
    {
      "name": "group_comfortable_friend",
      "description": " My group is a place to which I'd feel comfortable bringing a friend",
      "value": "1. (1) Strongly disagree,\n2. (2) Disagree,\n3. (3) Neither agree nor disagree,\n4. (4) Agree,\n5. (5) Strongly agree",
      "@type": "propertyValue"
    },
    {
      "name": "group_beliefs_humility",
      "description": " My group is a place where people express their beliefs with humility",
      "value": "1. (1) Strongly disagree,\n2. (2) Disagree,\n3. (3) Neither agree nor disagree,\n4. (4) Agree,\n5. (5) Strongly agree",
      "@type": "propertyValue"
    },
    {
      "name": "group_supports_action",
      "description": " My group supports me in taking action based on EA principles",
      "value": "1. (1) Strongly disagree,\n2. (2) Disagree,\n3. (3) Neither agree nor disagree,\n4. (4) Agree,\n5. (5) Strongly agree",
      "@type": "propertyValue"
    },
    {
      "name": "influence_80k_one_on_one",
      "description": "Influence your ability to make impact? 80,000 Hours (1-on-1 career discussion)",
      "@type": "propertyValue"
    },
    {
      "name": "influence_80k_website",
      "description": "Influence your ability to make impact? 80,000 Hours (website)",
      "@type": "propertyValue"
    },
    {
      "name": "influence_80k_podcast",
      "description": "Influence your ability to make impact? 80,000 Hours (podcast)",
      "@type": "propertyValue"
    },
    {
      "name": "influence_podcast_other",
      "description": "Influence your ability to make impact? Podcast (other than 80,000 Hours)",
      "@type": "propertyValue"
    },
    {
      "name": "influence_personal_contact",
      "description": "Influence your ability to make impact? Personal contact with EAs",
      "@type": "propertyValue"
    },
    {
      "name": "influence_books",
      "description": "Influence your ability to make impact? Books related to EA",
      "@type": "propertyValue"
    },
    {
      "name": "influence_gwwc",
      "description": "Influence your ability to make impact? Giving What We Can",
      "@type": "propertyValue"
    },
    {
      "name": "influence_local_group",
      "description": "Influence your ability to make impact? Local EA groups",
      "@type": "propertyValue"
    },
    {
      "name": "influence_givewell",
      "description": "Influence your ability to make impact? GiveWell",
      "@type": "propertyValue"
    },
    {
      "name": "influence_ea_global",
      "description": "Influence your ability to make impact? EA Global",
      "@type": "propertyValue"
    },
    {
      "name": "influence_eagx",
      "description": "Influence your ability to make impact? EAGx",
      "@type": "propertyValue"
    },
    {
      "name": "influence_ace",
      "description": "Influence your ability to make impact? Animal Charity Evaluators",
      "@type": "propertyValue"
    },
    {
      "name": "influence_lycs",
      "description": "Influence your ability to make impact? The Life You Can Save",
      "@type": "propertyValue"
    },
    {
      "name": "influence_ea_forum",
      "description": "Influence your ability to make impact? The EA Forum",
      "@type": "propertyValue"
    },
    {
      "name": "influence_articles_blogs",
      "description": "Influence your ability to make impact? Articles/blogs related to EA",
      "@type": "propertyValue"
    },
    {
      "name": "influence_ea_survey",
      "description": "Influence your ability to make impact? The EA Newsletter",
      "@type": "propertyValue"
    },
    {
      "name": "influence_facebook_groups",
      "description": "Influence your ability to make impact? Facebook groups related to EA",
      "@type": "propertyValue"
    },
    {
      "name": "influence_lesswrong",
      "description": "Influence your ability to make impact? LessWrong",
      "@type": "propertyValue"
    },
    {
      "name": "influence_slate_star",
      "description": "Influence your ability to make impact? Slate Star Codex",
      "@type": "propertyValue"
    },
    {
      "name": "influence_wanbam",
      "description": "Influence your ability to make impact? WANBAM",
      "@type": "propertyValue"
    },
    {
      "name": "influence_aac",
      "description": "Influence your ability to make impact? Animal Advocacy Careers",
      "@type": "propertyValue"
    },
    {
      "name": "influence_none",
      "description": "Influence your ability to make impact? None of the above",
      "@type": "propertyValue"
    },
    {
      "name": "influence_other",
      "description": "Influence your ability to make impact? Other",
      "@type": "propertyValue"
    },
    {
      "name": "negative_80k",
      "description": "Negative impact on your involvement with EA so far? 80,000 Hours",
      "@type": "propertyValue"
    },
    {
      "name": "negative_podcast",
      "description": "Negative impact on your involvement with EA so far? Podcast (not 80,000 Hours)",
      "@type": "propertyValue"
    },
    {
      "name": "negative_givewell",
      "description": "Negative impact on your involvement with EA so far? GiveWell",
      "@type": "propertyValue"
    },
    {
      "name": "negative_personal_contact",
      "description": "Negative impact on your involvement with EA so far? Personal contact with EAs",
      "@type": "propertyValue"
    },
    {
      "name": "negative_books",
      "description": "Negative impact on your involvement with EA so far? Books related to EA",
      "@type": "propertyValue"
    },
    {
      "name": "negative_gwwc",
      "description": "Negative impact on your involvement with EA so far? Giving What We Can",
      "@type": "propertyValue"
    },
    {
      "name": "negative_local_group",
      "description": "Negative impact on your involvement with EA so far? Local EA groups",
      "@type": "propertyValue"
    },
    {
      "name": "negative_lesswrong",
      "description": "Negative impact on your involvement with EA so far? LessWrong",
      "@type": "propertyValue"
    },
    {
      "name": "negative_slate_star",
      "description": "Negative impact on your involvement with EA so far? SlateStarCodex",
      "@type": "propertyValue"
    },
    {
      "name": "negative_ea_global",
      "description": "Negative impact on your involvement with EA so far? EA Global",
      "@type": "propertyValue"
    },
    {
      "name": "negative_eagx",
      "description": "Negative impact on your involvement with EA so far? EAGx",
      "@type": "propertyValue"
    },
    {
      "name": "negative_facebook_group",
      "description": "Negative impact on your involvement with EA so far? FB groups related to EA",
      "@type": "propertyValue"
    },
    {
      "name": "negative_ea_forum",
      "description": "Negative impact on your involvement with EA so far? The EA Forum",
      "@type": "propertyValue"
    },
    {
      "name": "negative_articles_blogs",
      "description": "Negative impact on your involvement with EA so far? Articles/blogs related EA",
      "@type": "propertyValue"
    },
    {
      "name": "negative_ea_fellowship",
      "description": "Negative impact on your involvement with EA so far? An EA Fellowship",
      "@type": "propertyValue"
    },
    {
      "name": "negative_eagx2",
      "description": "Negative impact on your involvement with EA so far? EAGx",
      "@type": "propertyValue"
    },
    {
      "name": "negative_ea_newsletter",
      "description": "Negative impact on your involvement with EA so far? The EA Newsletter",
      "@type": "propertyValue"
    },
    {
      "name": "negative_wanbam",
      "description": "Negative impact on your involvement with EA so far? WANBAM",
      "@type": "propertyValue"
    },
    {
      "name": "negative_none",
      "description": "Negative impact on your involvement with EA so far? None of the above",
      "@type": "propertyValue"
    },
    {
      "name": "negative_other",
      "description": "Negative impact on your involvement with EA so far? Other",
      "@type": "propertyValue"
    },
    {
      "name": "negative_response",
      "description": "Negative impact on your involvement with EA so far? Open-Ended Response",
      "@type": "propertyValue"
    },
    {
      "name": "engaged_ea_forum",
      "description": "Affected your likelihood of staying engaged with EA? The EA Forum",
      "value": "1. Made me a lot less likely to stay engaged,\n2. Made me less likely to stay engaged,\n3. Made me slightly less likely to stay engaged,\n4. Significant interaction, but neutral effect,\n5. Made me slightly more likely to stay engaged,\n6. Made me more likely to stay engaged,\n7. Made me a lot more likely to stay engaged",
      "@type": "propertyValue"
    },
    {
      "name": "engaged_online_community",
      "description": "Affected your likelihood of staying engaged with EA? The online EA community",
      "value": "1. Made me a lot less likely to stay engaged,\n2. Made me less likely to stay engaged,\n3. Made me slightly less likely to stay engaged,\n4. Significant interaction, but neutral effect,\n5. Made me slightly more likely to stay engaged,\n6. Made me more likely to stay engaged,\n7. Made me a lot more likely to stay engaged",
      "@type": "propertyValue"
    },
    {
      "name": "engaged_local_groups",
      "description": "Affected your likelihood of staying engaged with EA? Local EA groups",
      "value": "1. Made me a lot less likely to stay engaged,\n2. Made me less likely to stay engaged,\n3. Made me slightly less likely to stay engaged,\n4. Significant interaction, but neutral effect,\n5. Made me slightly more likely to stay engaged,\n6. Made me more likely to stay engaged,\n7. Made me a lot more likely to stay engaged",
      "@type": "propertyValue"
    },
    {
      "name": "engaged_ea_fellowship",
      "description": "Affected your likelihood of staying engaged with EA? An EA Fellowship",
      "value": "1. Made me a lot less likely to stay engaged,\n2. Made me less likely to stay engaged,\n3. Made me slightly less likely to stay engaged,\n4. Significant interaction, but neutral effect,\n5. Made me slightly more likely to stay engaged,\n6. Made me more likely to stay engaged,\n7. Made me a lot more likely to stay engaged",
      "@type": "propertyValue"
    },
    {
      "name": "engaged_gwwc",
      "description": "Affected your likelihood of staying engaged with EA? Giving What We Can",
      "value": "1. Made me a lot less likely to stay engaged,\n2. Made me less likely to stay engaged,\n3. Made me slightly less likely to stay engaged,\n4. Significant interaction, but neutral effect,\n5. Made me slightly more likely to stay engaged,\n6. Made me more likely to stay engaged,\n7. Made me a lot more likely to stay engaged",
      "@type": "propertyValue"
    },
    {
      "name": "engaged_ea_global",
      "description": "Affected your likelihood of staying engaged with EA? EA Global",
      "value": "1. Made me a lot less likely to stay engaged,\n2. Made me less likely to stay engaged,\n3. Made me slightly less likely to stay engaged,\n4. Significant interaction, but neutral effect,\n5. Made me slightly more likely to stay engaged,\n6. Made me more likely to stay engaged,\n7. Made me a lot more likely to stay engaged",
      "@type": "propertyValue"
    },
    {
      "name": "engaged_eagx",
      "description": "Affected your likelihood of staying engaged with EA? EAGx",
      "value": "1. Made me a lot less likely to stay engaged,\n2. Made me less likely to stay engaged,\n3. Made me slightly less likely to stay engaged,\n4. Significant interaction, but neutral effect,\n5. Made me slightly more likely to stay engaged,\n6. Made me more likely to stay engaged,\n7. Made me a lot more likely to stay engaged",
      "@type": "propertyValue"
    },
    {
      "name": "engaged_ea_newsletter",
      "description": "Affected your likelihood of staying engaged with EA? The EA Newsletter",
      "value": "1. Made me a lot less likely to stay engaged,\n2. Made me less likely to stay engaged,\n3. Made me slightly less likely to stay engaged,\n4. Significant interaction, but neutral effect,\n5. Made me slightly more likely to stay engaged,\n6. Made me more likely to stay engaged,\n7. Made me a lot more likely to stay engaged",
      "@type": "propertyValue"
    },
    {
      "name": "engaged_wanbam",
      "description": "Affected your likelihood of staying engaged with EA? WANBAM",
      "value": "1. Made me a lot less likely to stay engaged,\n2. Made me less likely to stay engaged,\n3. Made me slightly less likely to stay engaged,\n4. Significant interaction, but neutral effect,\n5. Made me slightly more likely to stay engaged,\n6. Made me more likely to stay engaged,\n7. Made me a lot more likely to stay engaged",
      "@type": "propertyValue"
    },
    {
      "name": "engaged_personal_contact",
      "description": "Affected your likelihood of staying engaged with EA? Personal contacts",
      "value": "1. Made me a lot less likely to stay engaged,\n2. Made me less likely to stay engaged,\n3. Made me slightly less likely to stay engaged,\n4. Significant interaction, but neutral effect,\n5. Made me slightly more likely to stay engaged,\n6. Made me more likely to stay engaged,\n7. Made me a lot more likely to stay engaged",
      "@type": "propertyValue"
    },
    {
      "name": "engaged_80k_podcast",
      "description": "Affected your likelihood of staying engaged with EA? 80,000 Hours (podcast)",
      "value": "1. Made me a lot less likely to stay engaged,\n2. Made me less likely to stay engaged,\n3. Made me slightly less likely to stay engaged,\n4. Significant interaction, but neutral effect,\n5. Made me slightly more likely to stay engaged,\n6. Made me more likely to stay engaged,\n7. Made me a lot more likely to stay engaged",
      "@type": "propertyValue"
    },
    {
      "name": "engaged_80k_hours",
      "description": "Affected your likelihood of staying engaged with EA? 80,000 Hours (website)",
      "value": "1. Made me a lot less likely to stay engaged,\n2. Made me less likely to stay engaged,\n3. Made me slightly less likely to stay engaged,\n4. Significant interaction, but neutral effect,\n5. Made me slightly more likely to stay engaged,\n6. Made me more likely to stay engaged,\n7. Made me a lot more likely to stay engaged",
      "@type": "propertyValue"
    },
    {
      "name": "engaged_80k_one_on_one",
      "description": "Affected your likelihood of staying engaged with EA? 80k Hours (1-on-1 career)",
      "value": "1. Made me a lot less likely to stay engaged,\n2. Made me less likely to stay engaged,\n3. Made me slightly less likely to stay engaged,\n4. Significant interaction, but neutral effect,\n5. Made me slightly more likely to stay engaged,\n6. Made me more likely to stay engaged,\n7. Made me a lot more likely to stay engaged",
      "@type": "propertyValue"
    },
    {
      "name": "engaged_givewell",
      "description": "Affected your likelihood of staying engaged with EA? GiveWell",
      "value": "1. Made me a lot less likely to stay engaged,\n2. Made me less likely to stay engaged,\n3. Made me slightly less likely to stay engaged,\n4. Significant interaction, but neutral effect,\n5. Made me slightly more likely to stay engaged,\n6. Made me more likely to stay engaged,\n7. Made me a lot more likely to stay engaged",
      "@type": "propertyValue"
    },
    {
      "name": "engaged_lesswrong",
      "description": "Affected your likelihood of staying engaged with EA? LessWrong",
      "value": "1. Made me a lot less likely to stay engaged,\n2. Made me less likely to stay engaged,\n3. Made me slightly less likely to stay engaged,\n4. Significant interaction, but neutral effect,\n5. Made me slightly more likely to stay engaged,\n6. Made me more likely to stay engaged,\n7. Made me a lot more likely to stay engaged",
      "@type": "propertyValue"
    },
    {
      "name": "engaged_slate_star",
      "description": "Affected your likelihood of staying engaged with EA? Slate Star Codex",
      "value": "1. Made me a lot less likely to stay engaged,\n2. Made me less likely to stay engaged,\n3. Made me slightly less likely to stay engaged,\n4. Significant interaction, but neutral effect,\n5. Made me slightly more likely to stay engaged,\n6. Made me more likely to stay engaged,\n7. Made me a lot more likely to stay engaged",
      "@type": "propertyValue"
    },
    {
      "name": "substantial_affect_impact",
      "description": "Are there other things which have substantially affected your impact? ",
      "@type": "propertyValue"
    },
    {
      "name": "prioritize_animal_welfare",
      "value": "1. 1,\n2. 2,\n3. 3,\n4. 4,\n5. 5",
      "@type": "propertyValue"
    },
    {
      "name": "prioritize_causes",
      "value": "1. 1,\n2. 2,\n3. 3,\n4. 4,\n5. 5",
      "@type": "propertyValue"
    },
    {
      "name": "prioritize_climate_change",
      "value": "1. 1,\n2. 2,\n3. 3,\n4. 4,\n5. 5",
      "@type": "propertyValue"
    },
    {
      "name": "prioritize_biosecurity",
      "value": "1. 1,\n2. 2,\n3. 3,\n4. 4,\n5. 5",
      "@type": "propertyValue"
    },
    {
      "name": "prioritize_nuclear_security",
      "value": "1. 1,\n2. 2,\n3. 3,\n4. 4,\n5. 5",
      "@type": "propertyValue"
    },
    {
      "name": "prioritize_ai_risks",
      "value": "1. 1,\n2. 2,\n3. 3,\n4. 4,\n5. 5",
      "@type": "propertyValue"
    },
    {
      "name": "prioritize_mental_health",
      "value": "1. 1,\n2. 2,\n3. 3,\n4. 4,\n5. 5",
      "@type": "propertyValue"
    },
    {
      "name": "prioritize_global_poverty",
      "value": "1. 1,\n2. 2,\n3. 3,\n4. 4,\n5. 5",
      "@type": "propertyValue"
    },
    {
      "name": "prioritize_meta",
      "value": "1. 1,\n2. 2,\n3. 3,\n4. 4,\n5. 5",
      "@type": "propertyValue"
    },
    {
      "name": "prioritize_ea_movement",
      "value": "1. 1,\n2. 2,\n3. 3,\n4. 4,\n5. 5",
      "@type": "propertyValue"
    },
    {
      "name": "prioritize_x_risks",
      "value": "1. 1,\n2. 2,\n3. 3,\n4. 4,\n5. 5",
      "@type": "propertyValue"
    },
    {
      "name": "prioritize_broad_longtermism",
      "value": "1. 1,\n2. 2,\n3. 3,\n4. 4,\n5. 5",
      "@type": "propertyValue"
    },
    {
      "name": "prioritize_other",
      "description": "Are there any other causes you feel should be priorities for the EA community? ",
      "@type": "propertyValue"
    },
    {
      "name": "currency",
      "@type": "propertyValue"
    },
    {
      "name": "currency_other",
      "description": "Please select the currency that pertains to you. Other",
      "@type": "propertyValue"
    },
    {
      "name": "income",
      "description": "What was your pre-tax individual income in 2019? ",
      "@type": "propertyValue"
    },
    {
      "name": "donation_2019",
      "description": "In 2019, roughly how much money did you donate? ",
      "@type": "propertyValue"
    },
    {
      "name": "donation_2020",
      "description": "In 2020, how much do you currently plan to donate? ",
      "@type": "propertyValue"
    },
    {
      "name": "donate_later",
      "description": "Are you presently saving money to donate later, rather than donate now? ",
      "@type": "propertyValue"
    },
    {
      "name": "university_original",
      "description": "If applicable, which university or universities did you attend? ",
      "@type": "propertyValue"
    },
    {
      "name": "birth_year",
      "description": "In which year were you born? ",
      "@type": "propertyValue"
    },
    {
      "name": "gender_original",
      "description": "Gender, original ",
      "@type": "propertyValue"
    },
    {
      "name": "sexual_orientation",
      "description": "What is your sexual orientation? ",
      "@type": "propertyValue"
    },
    {
      "name": "country",
      "@type": "propertyValue"
    },
    {
      "name": "city_other",
      "description": "In what town/city/metropolitan area do you live? Other",
      "@type": "propertyValue"
    },
    {
      "name": "ea_community_ideal",
      "description": "How well does the EA community compare to your ideal? ",
      "@type": "propertyValue"
    },
    {
      "name": "ea_community_satisfaction",
      "description": "What is your overall satisfaction with the EA community? ",
      "@type": "propertyValue"
    },
    {
      "name": "ea_community_why",
      "description": "Why did you give the two ratings above? Open-Ended Response",
      "@type": "propertyValue"
    },
    {
      "name": "agree_ea_helps_impact",
      "description": "Agree: The EA community helps me have more impact.",
      "value": "1. (1) Strongly disagree,\n2. (2) Disagree,\n3. (3) Neither agree nor disagree,\n4. (4) Agree,\n5. (5) Strongly agree",
      "@type": "propertyValue"
    },
    {
      "name": "agree_part_of_ea_community",
      "description": "Agree: I feel that I am a part of the effective altruism community.",
      "value": "1. (1) Strongly disagree,\n2. (2) Disagree,\n3. (3) Neither agree nor disagree,\n4. (4) Agree,\n5. (5) Strongly agree",
      "@type": "propertyValue"
    },
    {
      "name": "friend_introduce",
      "description": "How excited would you be to introduce a friend to the EA community? ",
      "@type": "propertyValue"
    },
    {
      "name": "learned_80k",
      "description": " 80,000 Hours - Changed mind or learned something important",
      "@type": "propertyValue"
    },
    {
      "name": "connection_80k",
      "description": " 80,000 Hours - New interesting and valuable connection",
      "@type": "propertyValue"
    },
    {
      "name": "learned_ea_global",
      "description": " EA Global - Changed mind or learned something important",
      "@type": "propertyValue"
    },
    {
      "name": "connection_ea_global",
      "description": " EA Global - New interesting and valuable connection",
      "@type": "propertyValue"
    },
    {
      "name": "learned_ea_hub",
      "description": " EA Hub - Changed mind or learned something important",
      "@type": "propertyValue"
    },
    {
      "name": "connection_ea_hub",
      "description": " EA Hub - New interesting and valuable connection",
      "@type": "propertyValue"
    },
    {
      "name": "learned_ea_student_mentoring",
      "description": " EA Student Career Mentoring - Changed mind or learned something important",
      "@type": "propertyValue"
    },
    {
      "name": "connection_ea_student_mentor",
      "description": " EA Student Career Mentoring - New interesting and valuable connection",
      "@type": "propertyValue"
    },
    {
      "name": "learned_eagx",
      "description": " EAGx - Changed mind or learned something important",
      "@type": "propertyValue"
    },
    {
      "name": "connection_eagx",
      "description": " EAGx - New interesting and valuable connection",
      "@type": "propertyValue"
    },
    {
      "name": "learned_effective_thesis",
      "description": " Effective Thesis - Changed mind or learned something important",
      "@type": "propertyValue"
    },
    {
      "name": "connection_effective_thesis",
      "description": " Effective Thesis - New interesting and valuable connection",
      "@type": "propertyValue"
    },
    {
      "name": "learned_facebook_group",
      "description": " Facebook groups related to EA - Changed mind or learned something important",
      "@type": "propertyValue"
    },
    {
      "name": "connection_facebook_group",
      "description": " Facebook groups related to EA - New interesting and valuable connection",
      "@type": "propertyValue"
    },
    {
      "name": "learned_gwwc",
      "description": " Giving What We Can - Changed mind or learned something important",
      "@type": "propertyValue"
    },
    {
      "name": "connection_gwwc",
      "description": " Giving What We Can - New interesting and valuable connection",
      "@type": "propertyValue"
    },
    {
      "name": "learned_intl_ea_events",
      "description": " International EA social events - Changed mind or learned something important",
      "@type": "propertyValue"
    },
    {
      "name": "connection_intl_ea_events",
      "description": " International EA social events - New interesting and valuable connection",
      "@type": "propertyValue"
    },
    {
      "name": "learned_personal_connection",
      "description": " A personal connection - Changed mind or learned something important",
      "@type": "propertyValue"
    },
    {
      "name": "connection_personal_contact",
      "description": " A personal connection - New interesting and valuable connection",
      "@type": "propertyValue"
    },
    {
      "name": "learned_lesswrong",
      "description": " LessWrong - Changed mind or learned something important",
      "@type": "propertyValue"
    },
    {
      "name": "connection_lesswrong",
      "description": " LessWrong - New interesting and valuable connection",
      "@type": "propertyValue"
    },
    {
      "name": "learned_local_group",
      "description": " Local EA groups - Changed mind or learned something important",
      "@type": "propertyValue"
    },
    {
      "name": "connection_local_groups",
      "description": " Local EA groups - New interesting and valuable connection",
      "@type": "propertyValue"
    },
    {
      "name": "learned_non_local_group",
      "description": " Non-local meetups - Changed mind or learned something important",
      "@type": "propertyValue"
    },
    {
      "name": "connection_non_local_group",
      "description": " Non-local meetups - New interesting and valuable connection",
      "@type": "propertyValue"
    },
    {
      "name": "learned_ea_forum",
      "description": " The EA Forum - Changed mind or learned something important",
      "@type": "propertyValue"
    },
    {
      "name": "connection_ea_forum",
      "description": " The EA Forum - New interesting and valuable connection",
      "@type": "propertyValue"
    },
    {
      "name": "learned_ea_books",
      "description": " EA books - Changed mind or learned something important",
      "@type": "propertyValue"
    },
    {
      "name": "connection_ea_books",
      "description": " EA books - New interesting and valuable connection",
      "@type": "propertyValue"
    },
    {
      "name": "learned_ea_newsletter",
      "description": " The EA Newsletter - Changed mind or learned something important",
      "@type": "propertyValue"
    },
    {
      "name": "connection_ea_newsletter",
      "description": " The EA Newsletter - New interesting and valuable connection",
      "@type": "propertyValue"
    },
    {
      "name": "learned_none",
      "description": " None of the above - Changed mind or learned something important",
      "@type": "propertyValue"
    },
    {
      "name": "connection_none",
      "description": " None of the above - New interesting and valuable connection",
      "@type": "propertyValue"
    },
    {
      "name": "learned_connection_other",
      "description": " Other (please specify)",
      "@type": "propertyValue"
    },
    {
      "name": "participate_doing_good_better",
      "description": "Interested in: A reading group to discuss Doing Good Better",
      "@type": "propertyValue"
    },
    {
      "name": "participate_the_precipice",
      "description": "Interested in: A reading group to discuss The Precipice",
      "@type": "propertyValue"
    },
    {
      "name": "participate_fellowship_intro",
      "description": "Interested in: A fellowship covering the basics of effective altruism",
      "@type": "propertyValue"
    },
    {
      "name": "participate_fellowship_adv",
      "description": "Interested in: A fellowship covering advanced principles of effective altruism",
      "@type": "propertyValue"
    },
    {
      "name": "participate_80k_pod_discuss",
      "description": "Interested in: An 80,000 Hours podcast discussion group",
      "@type": "propertyValue"
    },
    {
      "name": "participate_fellowship_career",
      "description": "Interested in: A 4-part fellowship using the 80k tool for career planning",
      "@type": "propertyValue"
    },
    {
      "name": "participate_fellowship_causes",
      "description": "Interested in: A  fellowship covering key ideas related to your top cause area",
      "@type": "propertyValue"
    },
    {
      "name": "participate_intro_one_on_one",
      "description": "Interested in: An introductory 1-on-1 convo to discuss the basic ideas of EA",
      "@type": "propertyValue"
    },
    {
      "name": "participate_gwwc_info_session",
      "description": "Interested in: A one-time information session about GWWC / Try Giving",
      "@type": "propertyValue"
    },
    {
      "name": "participate_donation_discuss",
      "description": "Interested in: A one-time discussion about where other EAs are donating",
      "@type": "propertyValue"
    },
    {
      "name": "participate_social_event",
      "description": "Interested in: A one-time (virtual) social event to meet local EAs",
      "@type": "propertyValue"
    },
    {
      "name": "participate_contact",
      "description": "May we (CEA) contact you if the activit(ies) you selected become(s) available? ",
      "@type": "propertyValue"
    },
    {
      "name": "email_next_survey",
      "description": " Please send me an e-mail to next year's survey",
      "@type": "propertyValue"
    },
    {
      "name": "email_followup_surveys",
      "description": " Please e-mail me relevant followup surveys",
      "@type": "propertyValue"
    },
    {
      "name": "email_dont_email",
      "description": " Don't e-mail me about future surveys",
      "@type": "propertyValue"
    },
    {
      "name": "share_80k",
      "description": " Yes - I give my permission for this information to be shared with 80,000 Hours",
      "@type": "propertyValue"
    },
    {
      "name": "dont_share_80k",
      "description": " No - I do not wish for any of my information to be shared with 80,000 Hours",
      "@type": "propertyValue"
    },
    {
      "name": "profile_ea_hub",
      "description": "Would you like a personal profile on the EA Hub? ",
      "@type": "propertyValue"
    },
    {
      "name": "agree_quantify_compare_impact",
      "description": "Agree: It's possible to roughly quantify and compare different types of impact",
      "value": "1. (1) Strongly disagree,\n2. (2) Disagree,\n3. (3) Slightly disagree,\n4. (4) Neither agree nor disagree,\n5. (5) Slightly agree,\n6. (6) Agree,\n7. (7) Strongly agree",
      "@type": "propertyValue"
    },
    {
      "name": "agree_ways_better_than_others",
      "description": "Agree: Some ways of doing good are substantially better than others",
      "value": "1. (1) Strongly disagree,\n2. (2) Disagree,\n3. (3) Slightly disagree,\n4. (4) Neither agree nor disagree,\n5. (5) Slightly agree,\n6. (6) Agree,\n7. (7) Strongly agree",
      "@type": "propertyValue"
    },
    {
      "name": "agree_work_on_any_cause",
      "description": "Agree: It makes sense to be open to working on any cause",
      "value": "1. (1) Strongly disagree,\n2. (2) Disagree,\n3. (3) Slightly disagree,\n4. (4) Neither agree nor disagree,\n5. (5) Slightly agree,\n6. (6) Agree,\n7. (7) Strongly agree",
      "@type": "propertyValue"
    },
    {
      "name": "agree_farmed_animals_concern",
      "description": "Agree: Farmed animals deserve our moral concern",
      "value": "1. (1) Strongly disagree,\n2. (2) Disagree,\n3. (3) Slightly disagree,\n4. (4) Neither agree nor disagree,\n5. (5) Slightly agree,\n6. (6) Agree,\n7. (7) Strongly agree",
      "@type": "propertyValue"
    },
    {
      "name": "agree_longtermism",
      "description": "Agree: The impact of our actions on the very long-term future is most important",
      "value": "1. (1) Strongly disagree,\n2. (2) Disagree,\n3. (3) Slightly disagree,\n4. (4) Neither agree nor disagree,\n5. (5) Slightly agree,\n6. (6) Agree,\n7. (7) Strongly agree",
      "@type": "propertyValue"
    },
    {
      "name": "reputation_effect_explanation",
      "description": "If possible, could you please explain your answer? ",
      "@type": "propertyValue"
    },
    {
      "name": "bottleneck_productivity",
      "description": "Are there any things which you think currently bottleneck your positive impact? ",
      "@type": "propertyValue"
    },
    {
      "name": "dislike_ea_community",
      "description": "What do you personally dislike about the EA community and EA/EA-adjacent ideas? ",
      "@type": "propertyValue"
    },
    {
      "name": "donate_rethink_charity",
      "description": "Roughly how much did you donate in 2019? Rethink Charity",
      "@type": "propertyValue"
    },
    {
      "name": "donate_80k",
      "description": "Roughly how much did you donate in 2019? 80,000 Hours",
      "@type": "propertyValue"
    },
    {
      "name": "donate_center_applied_rational",
      "description": "Roughly how much did you donate in 2019? Center For Applied Rationality",
      "@type": "propertyValue"
    },
    {
      "name": "donate_mercy_for_animals",
      "description": "Roughly how much did you donate in 2019? Mercy For Animals",
      "@type": "propertyValue"
    },
    {
      "name": "donate_other1",
      "description": "Roughly how much did you donate in 2019? Other (please specify)",
      "@type": "propertyValue"
    },
    {
      "name": "donate_other2",
      "description": "Roughly how much did you donate in 2019? Other 2 (please specify)",
      "@type": "propertyValue"
    },
    {
      "name": "donate_other3",
      "description": "Roughly how much did you donate in 2019? Other 3 (please specify)",
      "@type": "propertyValue"
    },
    {
      "name": "donate_other4",
      "description": "Roughly how much did you donate in 2019? Other 4 (please specify)",
      "@type": "propertyValue"
    },
    {
      "name": "donate_other5",
      "description": "Roughly how much did you donate in 2019? Other 5 (please specify)",
      "@type": "propertyValue"
    },
    {
      "name": "datecreated",
      "description": "Date Created",
      "@type": "propertyValue"
    },
    {
      "name": "group_name_original",
      "description": "",
      "@type": "propertyValue"
    },
    {
      "name": "group_name_manual",
      "description": "Group Name, manually assigned",
      "@type": "propertyValue"
    },
    {
      "name": "first_hear_qual",
      "description": "",
      "@type": "propertyValue"
    },
    {
      "name": "_merge",
      "description": "",
      "value": "1. master only (1),\n2. using only (2),\n3. matched (3),\n4. missing updated (4),\n5. nonmissing conflict (5)",
      "@type": "propertyValue"
    },
    {
      "name": "ea_id",
      "@type": "propertyValue"
    },
    {
      "name": "ea_id2",
      "@type": "propertyValue"
    },
    {
      "name": "ea_id3",
      "@type": "propertyValue"
    },
    {
      "name": "engagement",
      "value": "1. (1) No engagement,\n2. (2) Mild engagement,\n3. (3) Moderate engagement,\n4. (4) Considerable engagement,\n5. (5) High engagement",
      "@type": "propertyValue"
    },
    {
      "name": "capital_over_impact",
      "value": "1. Modestly prioritizing career capital,\n2. Modestly prioritizing immediate impact,\n3. N/A,\n4. Prioritizing both equally,\n5. Strongly prioritizing career capital,\n6. Strongly prioritizing immediate impact",
      "@type": "propertyValue"
    },
    {
      "name": "financial_instability",
      "value": "1. Always,\n2. Never,\n3. Often,\n4. Prefer not to answer,\n5. Rarely,\n6. Sometimes",
      "@type": "propertyValue"
    },
    {
      "name": "first_generation_student",
      "value": "1. No,\n2. Yes",
      "@type": "propertyValue"
    },
    {
      "name": "reputation_effect",
      "value": "1. No, no reputational consequences at all,\n2. Yes, a mix of reputational benefits and negative reputational costs,\n3. Yes, mostly negative reputational costs,\n4. Yes, mostly positive reputational benefits",
      "@type": "propertyValue"
    },
    {
      "name": "year_involved",
      "value": "1. 2009 or before,\n2. 2010,\n3. 2011,\n4. 2012,\n5. 2013,\n6. 2014,\n7. 2015,\n8. 2016,\n9. 2017,\n10. 2018,\n11. 2019,\n12. 2020,\n13. I don't remember",
      "@type": "propertyValue"
    },
    {
      "name": "first_hear_ea",
      "value": "1. I don't remember,\n2. 80,000 Hours,\n3. Animal Charity Evaluators,\n4. Book, article, or blog post,\n5. EA Global / EAGx,\n6. Educational course (e.g. lecture, class, MOOC),\n7. Facebook,\n8. GiveWell,\n9. Giving What We Can,\n10. LessWrong,\n11. Local or university EA group,\n12. One For The World,\n13. Other,\n14. Personal contact (e.g. friend, colleague, relative),\n15. Podcast,\n16. REG / EAF / FRI / The Swiss group,\n17. Search engine,\n18. Slate Star Codex,\n19. TED talk,\n20. The Life You Can Save (organization),\n21. Vox's Future Perfect",
      "@type": "propertyValue"
    },
    {
      "name": "city",
      "value": "1. Amsterdam,\n2. Auckland,\n3. Berlin,\n4. Boston / Cambridge (USA),\n5. Cambridge (UK),\n6. Canberra,\n7. Chicago,\n8. London,\n9. Los Angeles,\n10. Melbourne,\n11. New York City,\n12. Oslo,\n13. Other (please specify),\n14. Oxford,\n15. Philadelphia,\n16. SF Bay Area,\n17. Seattle,\n18. Stockholm,\n19. Sydney,\n20. Toronto,\n21. Vienna,\n22. Washington, DC,\n23. Zürich",
      "@type": "propertyValue"
    },
    {
      "name": "collector_source",
      "value": "1. 80K 2,\n2. 80K1,\n3. CE,\n4. CEA FB,\n5. EA FB,\n6. EA Forum,\n7. EA Forum backup,\n8. EA Newsletter,\n9. EAA newsletter?,\n10. EAS80K3,\n11. Email Invitation 1,\n12. GWWC,\n13. Groups FB,\n14. Groups newsletter?,\n15. Groups personal email?,\n16. Groups slack,\n17. Hangouts,\n18. LG Newsletter,\n19. LW,\n20. Reddit,\n21. SSC,\n22. Sharing,\n23. dankeamemes",
      "@type": "propertyValue"
    },
    {
      "name": "gender_manual",
      "value": "1. Other,\n2. Female,\n3. Male",
      "@type": "propertyValue"
    },
    {
      "name": "race_white",
      "description": "What is your race/ethnicity? White",
      "@type": "propertyValue"
    },
    {
      "name": "race_black_aa",
      "description": "What is your race/ethnicity? Black or African American",
      "@type": "propertyValue"
    },
    {
      "name": "race_hispanic_la_spanish",
      "description": "What is your race/ethnicity? Hispanic, Latino or Spanish Origin",
      "@type": "propertyValue"
    },
    {
      "name": "race_american_indian_alaskan",
      "description": "What is your race/ethnicity? American Indian or Alaskan Native",
      "@type": "propertyValue"
    },
    {
      "name": "race_asian",
      "description": "What is your race/ethnicity? Asian",
      "@type": "propertyValue"
    },
    {
      "name": "race_native_hawaiin_pacific",
      "description": "What is your race/ethnicity? Native Hawaiian or Other Pacific Islander",
      "@type": "propertyValue"
    },
    {
      "name": "race_prefer_no_answer",
      "description": "What is your race/ethnicity? Prefer not to answer",
      "@type": "propertyValue"
    },
    {
      "name": "race_other",
      "description": "What is your race/ethnicity? Other (please specify)",
      "@type": "propertyValue"
    },
    {
      "name": "race_",
      "value": "1. american_indian_alaskan,\n2. asian,\n3. black_aa,\n4. hispanic_la_spanish,\n5. native_hawaiin_pacific,\n6. other,\n7. prefer_no_answer,\n8. white",
      "@type": "propertyValue"
    },
    {
      "name": "status_employed_ft",
      "description": "Employment/student status? Employed, full-time",
      "@type": "propertyValue"
    },
    {
      "name": "status_employed_pt",
      "description": "Employment/student status? Employed, part time",
      "@type": "propertyValue"
    },
    {
      "name": "status_self_employed",
      "description": "Employment/student status? Self-employed",
      "@type": "propertyValue"
    },
    {
      "name": "status_not_employed_looking",
      "description": "Employment/student status? Not employed, but looking",
      "@type": "propertyValue"
    },
    {
      "name": "status_not_employed",
      "description": "Employment/student status? Not employed, but not looking",
      "@type": "propertyValue"
    },
    {
      "name": "status_homemaker_parent",
      "description": "Employment/student status? Homemaker / full-time parent",
      "@type": "propertyValue"
    },
    {
      "name": "status_retired",
      "description": "Employment/student status? Retired",
      "@type": "propertyValue"
    },
    {
      "name": "status_student_hs",
      "description": "Employment/student status? Student (high school)",
      "@type": "propertyValue"
    },
    {
      "name": "status_student_undergrad",
      "description": "Employment/student status? Student (undergraduate)",
      "@type": "propertyValue"
    },
    {
      "name": "status_student_masters",
      "description": "Employment/student status? Student (masters or equivalent)",
      "@type": "propertyValue"
    },
    {
      "name": "status_student_doctoral",
      "description": "Employment/student status? Student (doctoral degree or equivalent)",
      "@type": "propertyValue"
    },
    {
      "name": "status_student_other",
      "description": "Employment/student status? Student (other)",
      "@type": "propertyValue"
    },
    {
      "name": "status_prefer_no_answer",
      "description": "Employment/student status? Prefer not to answer",
      "@type": "propertyValue"
    },
    {
      "name": "status_",
      "value": "1. employed_ft,\n2. employed_pt,\n3. homemaker_parent,\n4. not_employed,\n5. not_employed_looking,\n6. prefer_no_answer,\n7. retired,\n8. self_employed,\n9. student_doctoral,\n10. student_hs,\n11. student_masters,\n12. student_other,\n13. student_undergrad",
      "@type": "propertyValue"
    },
    {
      "name": "career_still_deciding",
      "description": "Current career description? Still deciding what to pursue",
      "@type": "propertyValue"
    },
    {
      "name": "career_building_capital",
      "description": "Current career description? Building flexible career capital",
      "@type": "propertyValue"
    },
    {
      "name": "career_non_profit_ea",
      "description": "Current career description? Work at a non-profit (EA organization)",
      "@type": "propertyValue"
    },
    {
      "name": "career_non_profit",
      "description": "Current career description? Work at a non-profit (not an EA organization)",
      "@type": "propertyValue"
    },
    {
      "name": "career_for_profit_earn_to_give",
      "description": "Current career description? For profit (earning to give)",
      "@type": "propertyValue"
    },
    {
      "name": "career_for_profit",
      "description": "Current career description? For profit (not earning to give)",
      "@type": "propertyValue"
    },
    {
      "name": "career_academia",
      "description": "Current career description? Academia",
      "@type": "propertyValue"
    },
    {
      "name": "career_government",
      "description": "Current career description? Government",
      "@type": "propertyValue"
    },
    {
      "name": "career_think_tank_lobby",
      "description": "Current career description? Think tanks / lobbying / advocacy",
      "@type": "propertyValue"
    },
    {
      "name": "career_na",
      "description": "Current career description? N/A",
      "@type": "propertyValue"
    },
    {
      "name": "career_other",
      "description": "Current career description? Other",
      "@type": "propertyValue"
    },
    {
      "name": "career_",
      "value": "1. academia,\n2. building_capital,\n3. for_profit,\n4. for_profit_earn_to_give,\n5. government,\n6. na,\n7. non_profit,\n8. non_profit_ea,\n9. other,\n10. still_deciding,\n11. think_tank_lobby",
      "@type": "propertyValue"
    },
    {
      "name": "race",
      "@type": "propertyValue"
    },
    {
      "name": "age_approx",
      "description": "In which year were you born? ",
      "@type": "propertyValue"
    },
    {
      "name": "employ_status",
      "value": "1. Employed (FT or self),\n2. Other (pt, unemployed, retired, homemaker, declined),\n3. Student",
      "@type": "propertyValue"
    },
    {
      "name": "age_approx_ranges",
      "value": "1. [4, 23),\n2. [23, 26),\n3. [26, 29),\n4. [29, 34),\n5. [34, 120)",
      "@type": "propertyValue"
    },
    {
      "name": "age_approx_split",
      "value": "1. [4, 27),\n2. [27, 120)",
      "@type": "propertyValue"
    },
    {
      "name": "engagement_num",
      "@type": "propertyValue"
    },
    {
      "name": "engagement_f",
      "value": "1. (1) No engagement,\n2. (2) Mild engagement,\n3. (3) Moderate engagement,\n4. (4) Considerable engagement,\n5. (5) High engagement",
      "@type": "propertyValue"
    },
    {
      "name": "d_engage_3_5",
      "@type": "propertyValue"
    },
    {
      "name": "d_engage_4_5",
      "@type": "propertyValue"
    },
    {
      "name": "d_engage_5",
      "@type": "propertyValue"
    },
    {
      "name": "income_k",
      "@type": "propertyValue"
    },
    {
      "name": "d_male",
      "@type": "propertyValue"
    },
    {
      "name": "d_student",
      "@type": "propertyValue"
    },
    {
      "name": "d_live_usa",
      "@type": "propertyValue"
    },
    {
      "name": "prioritize_lt",
      "@type": "propertyValue"
    },
    {
      "name": "referrer",
      "value": "1. 80K hours,\n2. CEA FB,\n3. dankeamemes,\n4. EA FB,\n5. EA Forum,\n6. EA Newsletter,\n7. Email; opt-in from prev. EAS,\n8. Giving What We Can,\n9. Groups FB,\n10. Groups personal email,\n11. Groups slack,\n12. Less Wrong,\n13. Reddit,\n14. Shared link,\n15. SlateStarCodex (Reddit group),\n16. Other",
      "@type": "propertyValue"
    },
    {
      "name": "referrer_cat",
      "value": "1. 80K hours,\n2. EA Forum,\n3. EA Newsletter,\n4. Email; opt-in from prev. EAS,\n5. Giving What We Can,\n6. Groups (local),\n7. Less Wrong or SlateStarCodex-Reddit,\n8. Reddit,\n9. Shared link,\n10. Social media (FB/memes),\n11. Other",
      "@type": "propertyValue"
    },
    {
      "name": "referrer_min100",
      "value": "1. 80K hours,\n2. EA Forum,\n3. EA Newsletter,\n4. Email; opt-in from prev. EAS,\n5. Groups personal email,\n6. Groups slack,\n7. Shared link,\n8. Other",
      "@type": "propertyValue"
    },
    {
      "name": "referrer_cat2",
      "@type": "propertyValue"
    },
    {
      "name": "referrer_cat3",
      "@type": "propertyValue"
    },
    {
      "name": "engage_cats_1",
      "@type": "propertyValue"
    },
    {
      "name": "engage_cats_2",
      "@type": "propertyValue"
    },
    {
      "name": "start_date_quantiles",
      "value": "1. [0%, 20%),\n2. [20%, 40%],\n3. (40%, 60%],\n4. (60%, 80%],\n5. (80%, 100%]",
      "@type": "propertyValue"
    },
    {
      "name": "start_date_thirds_by_referrer",
      "value": "1. [0%, 33.33%),\n2. [33.33%, 66.67%],\n3. (66.67%, 100%]",
      "@type": "propertyValue"
    },
    {
      "name": "survey_willing",
      "@type": "propertyValue"
    },
    {
      "name": "donation_2019_c",
      "@type": "propertyValue"
    },
    {
      "name": "donation_2020_c",
      "@type": "propertyValue"
    },
    {
      "name": "income_c",
      "@type": "propertyValue"
    },
    {
      "name": "income_k_c",
      "@type": "propertyValue"
    },
    {
      "name": "income_c_imp",
      "@type": "propertyValue"
    },
    {
      "name": "don_share_inc_19",
      "@type": "propertyValue"
    },
    {
      "name": "don_share_inc_19_imp",
      "@type": "propertyValue"
    },
    {
      "name": "don_19_p1",
      "@type": "propertyValue"
    },
    {
      "name": "income_c_imp_k",
      "@type": "propertyValue"
    },
    {
      "name": "action_gwwc_f",
      "value": "1. 0,\n2. 1",
      "@type": "propertyValue"
    },
    {
      "name": "top_priority_rating",
      "@type": "propertyValue"
    },
    {
      "name": "avg_priority_rating",
      "@type": "propertyValue"
    },
    {
      "name": "mn_priority_rating",
      "@type": "propertyValue"
    },
    {
      "name": "lt_top_priority",
      "@type": "propertyValue"
    },
    {
      "name": "lt_above_mn_priority",
      "@type": "propertyValue"
    },
    {
      "name": "top_priority_rating_among_lt",
      "@type": "propertyValue"
    },
    {
      "name": "mn_priority_lt_rating",
      "@type": "propertyValue"
    },
    {
      "name": "start_date_qtl_by_referrer",
      "value": "1. [0%, 25%),\n2. [25%, 50%],\n3. (50%, 75%],\n4. (75%, 100%]",
      "@type": "propertyValue"
    }
  ]
}`